ubiquitous computer aided design: a broken promise or a sleeping beauty?

Computer-Aided Design 59 (2015) 161–175

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Computer-Aided Design

journal homepage: www.elsevier.com/locate/cad

Ubiquitous computer aided design: A broken promise or a SleepingBeauty?✩

Imre Horváth, Regine W. Vroom ∗

Faculty of Industrial Design Engineering, Delft University of Technology, The Netherlands

h i g h l i g h t s

• An overall account of the status of ubiquitous computing and technologies in CAD.• Penetration of ubiquitous computing remained insignificant in most applications.• Application of ubiquitous technologies did not lead to radically new functionalities.• Computer aided design steps over the paradigm of ubiquitous computing.• New CAD functionalities expected from the emerging new computer paradigms.

a r t i c l e i n f o

Keywords:Ubiquitous computingComputer aided designUbiquitous design enablersCompeting technology exploitationUbiquitous CAD applications

a b s t r a c t

As a novel computational approach, ubiquitous computing was emerging at the beginning of the 1980sand has reached a rathermature level by now. It assumes that computing can be available anywhere, any-time and in any context due to technological developments, social demands and calm implementations.Over the years, the opportunities of this computing paradigm have been explored and the benefits havebeen exploited successfully inmany application fields. This survey paper addresses ubiquitous computingfrom the perspective of enabling computer aided design. The specific objectives of the reported survey areto: (i) give an overall account of the current status of ubiquitous computing and technologies, (ii) cast lighton how ubiquitous computing has influenced the development of CAD systems, tools, and methods, and(iii) critically investigate future development opportunities of ubiquitous computing enabled computeraided design. First, the paper discusses the principles and typical technologies of ubiquitous computing.Then, the development and spectrum of the so-called standard computer aided design tasks are analyzedfrom a computational point of view. Afterwards, the already implemented design enabling functionalitiesare discussed and some additional functional possibilities are considered. The literature provides evidencethat ubiquitous computing has not managed to revolutionize the methodologies or the systems of com-puter aideddesign so far, thoughmany researchers intensively studied the affordances and the applicationpossibilities of ubiquitous technologies. One reason is that ubiquitous computing technologies had in thelast two decades to compete with other kinds of computational technologies, such as high-capacity com-puting, high-speed networking, immersive virtual reality, knowledge ontologies, smart software agents,mobile communication, etc., which had amuch stronger influence on the development of computer aideddesign methods and systems. In combination with the rather conservative and conventionalist industrialpractice of CAD system development and application, this may explain why the ubiquitous computingrevolution remained weak in computer aided design. The literature clearly indicates that application ofubiquitous technologies did not lead to radically new functionalities that could have been exploited bythe concerned industries. Consequently, it seems to be possible that computer aided design simply stepsover the paradigm of ubiquitous computing and expects new functionalities from the emerging new com-puting paradigms, such as brain–computer interfacing, cyber–physical computing, biological computing,or quantum computing.

© 2014 Elsevier Ltd. All rights reserved.

✩ This paper has been recommended for acceptance by Dr. Kunwoo Lee.∗ Corresponding author.

E-mail addresses: [email protected] (I. Horváth), [email protected](R.W. Vroom).

http://dx.doi.org/10.1016/j.cad.2014.10.0060010-4485/© 2014 Elsevier Ltd. All rights reserved.

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162 I. Horváth, R.W. Vroom / Computer-Aided Design 59 (2015) 161–175

1. Introduction

1.1. Setting the stage

We have been witnessing a rapid evolution of computing, vi-sualization, networking, sensing, communication and informingparadigms, technologies and systems over the last sixty years [1].Technology historians refer to this period as the fourth industrialrevolution [2] (or as the digital revolution [3], or even as the intelli-gence revolution [4]). The digital revolution (DR) has placed infor-mation and knowledge into the position of an industrial economicasset, likewise the first and the second industrial revolutions did itwithmaterials and energies, respectively. It has also fundamentallychanged the relationship of people to information by: (i) replacingthe conventional paper-based recording of information by a digi-tal representation of information, (ii) providing immediate accessto repositories of information, (iii) offering various forms of digitalmedia for representation of information, (iv) availingmassive com-puting and storage capacities on demand, (v) enabling efficient al-phanumerical, numerical and graphical processing of information,(vi) making possible to communicate information over geograph-ical boundaries, and (vii) fostering digital assistance and automa-tion of business and production processes. The engine behind DRis the fast growing scientific knowledge, sophistication of digitaltechnologies, striving after ecologically, economically and sociallysustainable products and services, and the need for innovation toaddress industrial and social challenges [5]. DR influences a num-ber of major trends [6].

The still commencing DR involves a number of shifts in theparadigms of digital information processing (Fig. 1). It startedwith the development and application of centralized mainframecomputers that could be accessed simultaneously (and also re-motely) by many users through various peripheral devices. Thecomputing power of mainframe computers were mainly utilizedin alphanumerical data processing, graphical visualization, remotecommunication, data storage, and user–system interaction. At thebeginning of the 1980s, the paradigm of networked personal com-puting popped up and proliferated rapidly. This not only providedcomputing power and data storage sufficient for creative engineer-ing work, such as computer graphics and computer aided design,but also facilitated digital connectivity through the Internet and di-rect access to web-based contents and repositories. By 1984, morepeople used personal computers than mainframe computers. Net-working has developed into four categories: (i) master–slave satel-lite networking, (ii) node-centered wired networking, (iii) cellularwireless networking, and (iv) ad hoc hybrid networking. Network-ing facilitated novel forms of distributed computing such as gridand cloud computing. The evolution of digital data processing isgraduallymaking possible to capture semantics of information andthe context of computing and communication.

The technological developments, such as continuing miniatur-ization, the increase of capacities and performance, the reducedpower demand, and the decrease of production and operation costsof computing technologies, have facilitated a third wave of com-puting, which is referred to as ubiquitous computing [7,8], or alter-natively pervasive computing [9,10]. The former term is usedwhenthe emphasis is put on the opportunity of humans to have access tocomputing and to usemultiple computing devices from anywhere,any time, and in any form, also nomadically [11], while the latterterm is used to express that computing is (invisibly) embedded ineverything in an all-embracing connectivity. These have been cre-ating: (i) a kind of permeating computational thinking [12], (ii) anew relationship between human, information and computing re-sources, (iii) not-yet-completely understood personal, social, cul-tural, and economic impacts, and (iv) a new situation for system,product and service developers and designers.

Ubiquitous computing based products can be designed so asto be networked, portable, wearable, embeddable, and even im-plantable. The currently used wireless information appliances areable to connect to mobile phone networks, as well as to local In-ternet networks, in an ad hoc manner. Lyytinen and Yoo identi-fied two dimensions of ubiquitous computing, namely the level ofembeddedness (LoE), and the level of mobility (LoM). Accordingto their interpretation, traditional business computing is charac-terized by a low LoE and a low LoM, mobile computing by a highLoM and a low LoE, pervasive computing by a low LoM and a highLoE, and ubiquitous computing is characterized by a high LoE and ahigh LoM [13]. Independence from location and access modalitiesof computing has lent itself to the movement of computer tech-nologies from the forefront of our daily routine activities to thebackground [14]. Observing that people continue to view mobilecomputing devices asmini-desktops, applications as programs thatrun on these devices, and the environment as a virtual space that auser enters to perform a task and leaves when the task is finished,Banavar et al. proposed to adopt three precepts of pervasive com-puting: (i) a device is a portal into an application/data space, not arepository of custom softwaremanaged by the user, (ii) an applica-tion is a means by which a user performs a task, not a piece of soft-ware that is written to exploit a device’s capabilities, and (iii) thecomputing environment is the user’s information-enhanced phys-ical surroundings, not a virtual space that exists to store and runsoftware [15].

1.2. Structure of the paper

In this paper we concentrate on the current state of the art ofusing ubiquitous computing in the development of design enablers(systems, tools and methods) [16]. The content of this paper hasbeen compiled based on the results of a keyword-based onlineliterature study (using Web of Science and Google Scholar), focusgroup sessions, and expert interviews. Without jumping into thedetails of our analysis, itmust be noted that the search for scholarlypublications and other documents on Google resulted in a ratherunexpected outcome. A search with the keyword ‘ubiquitouscomputing’ resulted inmore than 172,000 hits,while the keywords‘ubiquitous systems’ and ‘ubiquitous products’ resulted in about13,900 hits and 530 hits, respectively. Using the same searchengine, the keyword ‘ubiquitous design tools’ brought up 3 hits,the keyword ‘ubiquitous computer aided design’ provided 2 resultsand the keyword ‘ubiquitous design enablers’ did not match anyscientific articles, reports or patents. Considering the relativelylarge number of scientific publications on ubiquitous computingand its applications in other products, environments and services,the low number of hits on using ubiquitous technologies to extendthe functionality of computer aided design system and to createubiquitous design systems and tools was a surprising result.Consequently, in order to generate a proper information basis forthis paper, we had to consider the above mentioned two otherforms of explorative research too.

Evidential is that ubiquitous computing may be in principleassociated with all application fields of CAD. However, in thispaper we concentrate our attention to the fields where geometric,morphological, and structural modeling play a role [17,18]. Thesearemechanical, architectural, construction and electronic CAD. Thecontent of the paper is arranged in the following structure. In thenext section we recapitulate the main principles and technologiesof ubiquitous computing. In Section 3 we sketch up the historicaldevelopment line of computer aided design to show how it hasbeen influenced by the overall development of digital computing.In Section 4 we discuss what has happened towards ubiquitousCAD tools and systems so far, paying special attention to thenew functionalities which are supported by the affordances of

I. Horváth, R.W. Vroom / Computer-Aided Design 59 (2015) 161–175 163

Fig. 1. Shifting paradigms of digital computing.

ubiquitous computing. In Section 5, we reflect on the impactsof ubiquitous computing on computer aided design. Finally, inthe last section, in addition to presenting some propositions asconclusions, we mention future research opportunities.

2. Challenges, technologies and manifestations of ubiquitouscomputing

2.1. Challenges raised by ubiquitous computing

The frequently quoted statement of Weiser, namely that ‘‘ubiq-uitous computing is the method of enhancing computer use bymaking many computers available throughout the physical envi-ronment, but making them effectively invisible to the user’’, veryexpressively summarizes the essence and influence of ubiquitouscomputing [19]. Ubiquitous computing is a manifestation of ex-perimental computer science that intends to transfer information-interlinked technological means into a wide range of practicalapplications. The reasoning is that computers are ceasing to ex-ist as distinct entities and are being merged with the everydayobjects that people use in their daily tasks. This is made possibleby the continuously decreasing physical size, power consumption,production price, and ecological impact of computing devices, aswell as their ceaselessly increasing processing power, storage ca-pacity and communication bandwidth. As research in nanotech-nology andmicrosystems proliferates, computingmeans appear asminiature wireless devices and can easily be embedded in otherartifacts. They cannot only be furnished with, but can also ag-gregate and generate information and knowledge. Thus everydayobjects are becoming smart and capable to operate and make de-cisions under varying circumstances. In this context, digital com-putation manifests as an enabling infrastructure in which not theincluded computing facilities, but the services that are producedby their smart, distributed, networked, and collaborating operationare playing the central role.

Design, development and implementation of smart and in-telligent, embedded or stand-alone ubiquitous computing envi-ronments are seen as radically different from traditional desktopcomputing environments. Actually, these have proven to be chal-lenging tasks with a strong need to address many technologi-cal, social, organizational and ecological aspects. Based on thework of Lyytinen et al., the challenges and issues raised by ubiq-uitous computing-based systems can be classified and summa-rized as: (i) application (relevance, usability, context-awareness,pro-activeness, personalization, efficiency, power consumption,sustainability, third-party services, limitations), (ii) networking(multi-connectivity, indoor and outdoor networking, mobile net-working, wireless networking, area of networks, performance,dependability, location management, bandwidth, resource al-location, protocols, quality of service, number of users, over-provisioning, informing), (iii) access (availability, distribution,decentralization, access-points, transactions, heterogeneity, com-plexity, transparency, interaction, feedback, immediacy), (iv) data

Fig. 2. Classes of technologies used in ubiquitous systems.

management (generating, searching, storage, replication, handling,update, synchronization, archiving, indexing, structuring, knowl-edge extraction, servicing, personalization) (v) security (strategy,intensiveness, confidentiality, authentication, integrity, authoriza-tion, non-repudiation, accessibility, standardization), (vi) impact(user privacy, information load, unpredictability, obtrusiveness,discomfort, measuring effects, context switches, task quality) and(vii) other related issues (multiple interactions, intelligence, fault-tolerance, ease-of-use,multi-functionality,multi-modality, specialfeatures) [20]. In the literature a large number of design principleshave been published related to practically each issue.

2.2. Ubiquitous technologies

A generic ubiquitous system is typically based on the spe-cific technologies shown in Fig. 2. They include a great varietyof capturing, processing, connecting, storage, and imaging tech-nologies. The processing and storage technologies are becomingmore andmore interlinked as utility, grid and cloud computing areused to harness shared computational resources in order to opti-mallymeet various demands in a timely and cost-effectivemanner[21,22]. Within conversion technologies, visualization and sensa-tion conversion technologies (including haptic, tactile, audio, etc.technologies) are differentiated,which support both input andout-put functions.

Sensing technologies include both hardware sensing andsoftware sensing technologies. Michahelles and Schiele publisheda reference table that sorts sensor technologies with respect to sixsensing dimensions, namely, (i) user’s ID, (ii) location, (iii) activity,(iv) object use, (v) bio signs/emotions, and (vi) human interactionand four sensor placement possibilities: in environment, onhuman, on object, and in mutual collaboration [23]. Adaptivewireless sensor networks are in the focus of current research [24].


Exploration technologies comprise search and data/knowledgemining technologies. Major exploration technologies are: commoninternet search, pattern-based discovery and object retrieval,context/semantics-driven search, and big data analytics [25–27].

Transmission technologies are for point-to-point transfer of sig-nals and data in bothwired andwireless forms [28–30]. Ramasamyand Sankaranarayanan surveyed the routing protocols developedfor the management of self-organizing hierarchical mobile ad hocnetworks (MANETs) [31]. Their classification includes: (i) routinginformation update mechanism (proactive or table-driven routingprotocols, reactive or on-demand routing protocols, hybrid routingprotocols), (ii) using temporal information (routing protocols usingpast temporal information, routing protocol that use future tem-poral information), (iii) using topology information (flat topologyrouting protocols, hierarchical topology routing protocols), andutilization of specific resources (power-aware routing, geographi-cal information assisted routing). Networking technologies involveboth fix node and ad hoc node networking technologies [32,33].

Actuator technologies have received strong attention in roboticssystem research, micro-electromechanical system research, andbio-engineering applications [34,35]. In robotics applications, typ-ical actuators are: (i) direct and geared drive motors, (ii) elec-tromechanical grabbing hands, (iii) hydraulic and pneumatic arms,(iv) piezoelectric and magnetostrictive actuators, and (v) shapememory and contractile polymer actuators [36,37]. Kim et al.identified three forms of ubiquitous robotics, including: soft-ware robots (sobot), embedded robots (embot), and mobile robots(mobot), which provide various services by any device, throughany network, at any place, anytime in a ubiquitous space [38].

Ubiquitous computing related powering technologies are con-stant (power network), periodic (e.g. wind generated), and volatile(e.g. battery) electric energy sources [39–41]. Due to this widerange and variability of the hardware and software technologies,the application scenarios of ubiquitous computing feature manyfunctions, such as ‘sense’, ‘infer’, ‘control’ and ‘actuate’, which com-plement the traditional ‘compute’, ‘visualize’ or ‘communicate’functions [42].

2.3. Forms of manifestation

Ubiquitous computing has no single point of beginning [43].Since the time of its emergence, its main challenge was findingprospective ways of moving beyond desktop computing. In thiscontext, four perspectives have been put forward (Fig. 3). The firstone is the perspective of ambient computing, which claims thatnew functionalities can be realized if computers are embeddedeverywhere in the environment, designed to be alert (constantlyavailable), able to sense users’ presence and situations and to actand interact accordingly. The second one is the perspective a mo-bile computing, which assumes that computational means can beembedded in mobile/portable hand-held devices such as PDAs,smartphones, tablets (and other solutions currently conceptual-ized on patent level) can be designed to interact with both the userand the ‘digital environment’ [44]. The third one is the perspectiveof wearable computing, which exploits the growing opportunity ofintegrating electronic devices into human-worn cloths or makingpossible to wear them as body accessories [45]. The fourth one isthe perspective of invisible computing that assumes that anythingcan be a computer in the future, as promised by the tenet of quan-tum computing, the next wave of computing.

Blending of dispersed computing, flexible networking, contextawareness, and accessible web repositories have led to what iscalled intelligent ambient environments (also referred to as ambi-ent intelligence or context-aware computing) [46,47]. Research inambient environments looks back to a relatively long history [48].

Fig. 3. Four perspectives of ubiquitous computing.

The idea of using ambient computing and intelligence for the bene-fit of people in their everyday life got into the focus of researcherssome twenty years ago. One of the first overviews of the oppor-tunities (and an analysis of different use scenarios) was publishedby Pentland, who concentrated on smart rooms [49]. He describedthem as computing-augmented living spaces, which are able to:(i) identify people, (ii) interpret their actions, (iii) support theiractivities, (iv) influence their mood, feelings and relationships,and (v) feature embodied interaction. It has to be noted these areachieved by applying different principles, technologies and meth-ods than those typical in the case of virtual or augmented reality-based immersive environments [50]. For instance, the knowledgeof affective computing and emotional engineering has been consid-ered to detect and influence the mood and feelings of people [51].The research and development issues of smart homes wereaddressed from both historical and technological perspectives[52–54]. The infrastructure of ubiquitous computing environmentsmay be organized and structured as a cyber-equivalent of anecosystem, that is, a very complex and dynamic infrastructure. Thepaper of von Reischach provides a comprehensive design spacefor product recommendations in the ubiquitous computing do-main [55]. The paper also offers a visual notation for the designspace that allows categorizing existing and envisioned systems.Lupiana et al. proposed a classification of ubiquitous computingenvironments. They differentiated between interactive environ-ments (support group events), including creative spaces andmeet-ing spaces, and smart environments, including ambient spaces andsmart spaces [56]. Roalter et al. discussed that one of the main andstill unsolved problems for researchers in the domain of intelligentenvironments is a suitable middleware [57]. They argued that theproposed systems and tools, with the presented extensions andnovelties, are suitable to allow for a significant reduction in effortsand complexity, while maintaining a high degree of flexibility andpossibilities for reuse.

Mobile computing means utilization of computational meansand capacity ‘on-the-go’, e.g., while traveling, or working on asite [58]. It assumes possibility of making network connectionsin multiple forms while changing spatial position, and therebyof searching, visualization, data input, and communication [14].This is contrasted by the idea of nomadic computing, which isalso based on the use of ‘portable’ devices, but no mobility whileconnected [59]. Due to size, resolution and speed issues, processinglarge contents is not yet solved in the context of mobile devices,though many researchers dealt with the issue. The reason is thatoften there is a need not only for a representation conversion,but also for a semantic or even pragmatic transformation [60].Forman and Zahorjan investigated the challenges of mobilecomputing [61]. Mobile computing plays an important role inmobile industrial robotics, intelligent transportation, and locationchange of humans [62–64], where context-dependent operation


is an issue [65]. There are some typical results of the researcherswho addressed the representation, semantic and pragmatictransformation issues. For instance, Qiu et al. proposed a methodfor geometric model simplification for distributed CAD in orderto allow real time collaboration [66]. Yang proposed an approachto CAD data visualization on mobile devices using constrainedDelaunay triangulation [67]. Kim and Albers addressed Webdesign issues when searching for information in a small screendisplay [68]. Luigina and Liam addressed the issue of designinghybrid museum space [69], and Oppermann and Specht developeda context-sensitive nomadic exhibition guide [70]. Nevertheless,Stackpole raised the issue if smartphones and tablet computerswill be able to detach engineers from their powerful multimediadesktop computers [71].

Wearable computing is about creating synergic relationshipsbetween human and animal body and computing instrumen-tation towards personal empowering and services. These sys-tems can be included in garment cloths, shoes, belts, and wrist-,neck-, head- or ankle-worn accessories. Mann, S. formulated sixbasic attributes for wearable computing such as: (i) unrestrictive(to activities), (ii) unmonopolizing (attention), (iii) observable(by user), (iv) controllable (infinitely), (v) attentive (to environ-ment), and (vi) communicative (expressive) [72,73]. As affor-dances of wearable computing, shared or photographic memory,collective intelligence, tetherless operation, personal safety, syn-ergistic combination, and enhancing experiences, are typicallymentioned. Rhodes et al. identified a number of limitations withwearable computing such as; (i) maintaining localized informa-tion, (ii) restricted scope, (iii) multitude of controls, and (iv) re-sourcemanagement [74]. Starner analyzed themajor challenges ofwearable computing and addressed the issue of human-poweredwearable computing [75].

The term ‘invisible computing’ is used in many different mean-ings in the related literature. For instance, it is used as an um-brella term to describe miniature-sized, embedded computingsolutions [76]. Waller and Johnston analyzed the notion of ‘in-visible information systems’ that are indistinguishable from theenvironment and collective work practices especially in routineoperational contexts [77]. Heer and Khooshabeh investigated twocomplementary concepts: (i) invisibility-in-use (the experienceof direct interaction with artifacts and tools), and (ii) infrastruc-tural invisibility (the capacity of physical, organizational, or tech-nological infrastructures to be tacitly present in thoughts andactions) [78]. Satyanarayanan interpreted invisibility as a ‘com-plete disappearance of pervasive computer technology from auser’s consciousness’ [10]. This interpretation blends invisibility-in-use with infrastructural invisibility. Tolmie et al. argued thatthe concept of invisible interfaces does not in any way imply lit-eral physical invisibility. Invisibility is an experienced relationshipbetween humans and their tools whether they are physical or con-ceptual [79]. In this paperwe refer to invisible computing as in vivoimplantable health systems to affect vital functions of humans, an-imal and plants, and to provide necessary artifacts and deliver ser-vices such as bio physiological implantation and medical therapy.These typically unobtrusive and automaticallyworking biomedicalsystems are equipped with sensors, wireless transceivers and datastorage technologies. Studied by Rehman, one important challengeis interaction with invisible computing devices [80], another is no-madic interaction [81].

2.4. Typical applications

Ubiquitous computing systems are alert and take actions ac-cording to environmental conditions or user requests. They applyboth explicit and implicit interfaces. The most frequently used ex-plicit interfacing modalities are such as (i) handwriting and sketch

based interfacing, (ii) hand motion and gesture recognition-basedinput and control, (iii) video-interfacing, (iv) voice and speechrecognition based interfacing, (v) on-screen/touch-panel interfac-ing, (vi) spatial and location information based control, (vii) physi-cal signal dependent control, (viii) hybrid interfacing technologies,and (ix) brain–computer interfacing. The lastly mentioned form ofinterfacing points into the future, while the other modalities rep-resent the results of the efforts researchers made in the last twodecades towards natural interfaces. They have also been put on thelist of objectives of virtual reality and tangible virtuality research.As formulated by Coyne, virtual reality research assumes that wecan construct correspondences between the world we inhabit andthe virtual world’s defined digital spaces, andwe can immerse our-selves in such spaces so that we experiencemore than in the phys-ical space [32].

Real world objects enriched with information processing capa-bilities are conceived to be able to operate smartly of even behaveintelligently. The terms ‘smart object’ and ‘intelligent object’ areoften (interchangeably) used to identify engineered solutions thatare able to: (i) recognize each other, (ii) act as a transitory com-munity of actors (that are aware of their belonging together), and(iii) form open, distributed and dynamic systems (that are able tomake decisions autonomously) [82]. Among others, the technolog-ical enablers of smart behavior are embeddedmulti-sensors, wire-less interconnection, artificial intelligence techniques, and locationor situation awareness [83]. Having these capabilities, productsare increasingly able to react on the changes in the environmentaround them, communicate with the agents of this environment,and thereby to optimize operation and improve efficiently [84].Typically three levels of smartness are differentiated in products:

• Level 1—products equipped with basic sensing mechanismand simple means of communicating any changes in theenvironment.

• Level 2—products having the ability of taking corrective actionsthrough embedded software in addition to having sensingability and a means of data communication.

• Level 3—productswhich have increased intelligence, a two-wayflow of communication, being connected through an Internet-based or wireless network, and having advanced capabilities ofdata collection, processing, reporting, and built in intelligenceto sense, reason and take corrective actions.

Survey of Meyer et al. gave insights in the technological founda-tions of intelligent products and proposed a classification whichdistinguishes between three orthogonal dimensions, namely: levelof intelligence, location of intelligence, and manifestation of intel-ligence [85].

Niskanen and Kantorovitch characterized future smart prod-ucts as systems that exploit advanced computation capabilities,aware of their surroundings, and able to support users in varioustasks [86]. Typical examples of smart system behavior are cars rec-ognizing the drivers, homes adapting to the mood of occupants,systems supervising crowds of people or safeguarding elderly peo-ple, and culminate in applications such as teaching robots, intel-ligent cars, or rehabilitation systems [87–89]. Eventually, withoutbeing aware of the context of operation, no product or system canbe smart. A smartphone normally rings, but it only softly buzzeswhen, based on the available GPS information, it concludes that theuser is in a theater. Context models have been proposed to includeall necessary information about the objects, circumstances, or con-ditions which a system is surrounded by, and which is neededfor semantic interpretation of these [90]. In practice, smartnessmanifests in proactive and/or responsive context-sensitive opera-tions and adaptation to users and environmental situations. Smart-ness and context-awareness together lend themselves to a situated


Fig. 4. Phases of evolution of CAD.

operation of systems [91]. For instance, Wagner and Arnfast im-plemented a context aware medication reminder system that re-sponds to the context of the user and only disturbs the user whenneeded [92]. It should be noted that ubiquitous systems are stillstruggling with sensing based capture of context since human ac-tivities, surroundings, and rationales are very diverse and usuallychange dynamically [93].

Ubiquitous systemsplace emphasis on the real (physical)world,rather than on the virtual or logical worlds [94]. Ubiquitous com-puting enables the development of massively distributed systemsthat help transform physical spaces into computationally activeand highly interactive smart spaces/environments. Nevertheless,they operate as information-intensive systems and should be ableto cope with uncertainties [95]. In other words, they generate andprocess large amount of data and knowledge, which usually needreal-timedistributedprocessing [96]. As discussedbyRanganathanand Campbell, ubiquitous computing environments may include alarge number of autonomous agents that work together [97]. Theagents sense and reason about the current context of the environ-ment and interact smoothly with other agents. Reffat and Beilharzproposed a framework of intelligent agents to support designingin virtual environments. The semantic-based agents exhibit thefollowing attributes in a virtual environment: autonomy, reactiv-ity, proactivity and social ability. Employing intelligent agents invirtual environments empowers computers not only to support amuch higher degree of visual realism, but also with processes ofintelligent behavior [98]. Smart design environment should pro-vide appropriate design support to its users. They capture designsemantics (high level relationships between objects) and incorpo-rate them into intelligent agents. These agents interact with ob-jects in the environment, monitor the actions of designers, andprovide design guidance and assistance. Researchers reported onvarious challenges, as well as research and development issues re-lated to data acquisition and management by and in ubiquitoussystems [99,100], which originate in their dynamic, distributed,heterogeneous, adaptive and autonomous nature [48,101].

Nowadays, direct communication between human brain andexternal devices is a progressively developing domain of researchand it receives attention frommany aspects [102,103]. AsWolpawand et al. postulated, brain–computer interfacing (BCI) is going toplay a crucial role in ubiquitous computing systems because of thepossibilities it offers for providing new augmentative communica-tion technology to thosewho aremotor paralyzed or have other se-veremovement or communication deficits [104]. The technologiesdeveloped for this purpose acquire various signals (EEG, ECoG, LFPand SU) from the human brain, and apply various signal process-ing techniques (Fourier transformation, autoregressions, wavelets

transformation, Laplacian filters, spatial filters) in order to gener-ate control information for various actuators (e.g., robotic arms,assistive robots). On the whole, BCI is currently still somewhat un-derexplored and underdeveloped domain of ubiquitous comput-ing [105].

3. Evolution and typical activities of computer aided design

3.1. Identifying evolutional phases of CAD

Computer aided design (CAD) can look back to a self-triggeredhistorical development plan [106]. Over the years, CAD was utiliz-ing the opportunities offered by general-purpose computing tech-nologies, except some cases in the old past, when a few peripheraldevices (like pen-plotters) were developed exclusively for the pur-pose of computer aided drawing or, later on, for interaction withsystems. From a bird-eye-view, the historical evolution of com-puter aided design resembles a sigmoid-curve, which shows slowtaking off, rapid and steep development, and slowing down again.This reflects the interplay between the available resources and theapplication opportunities.

In a somewhat higher resolution, the historical evolution en-compasses a number of development periods, whichwere broughtabout and triggered by: (i) shifting objectives in research anddevelopment, (ii) advancements of computational hardware andsoftware technologies, and (iii) aggregation of algorithm andmethodological knowledge. These periods have vague boundaries,therefore any effort to assign starting and ending years to them canbe nothing else but a semi-objective judgment. From the perspec-tive of academic research, we can identify the following periods:(i) establishment of the field of interest and the research commu-nity, (ii) consolidation and diversification, (iii) integration and net-working, (iv) virtualization and collaboration, and (v) permeationinto new domains [Fig. 4].

3.2. Establishment of the discipline

The first phase of CAD evolution happened roughly in the yearsbetween the beginning of 1960s and the beginning of the 1970s.This periodwas about establishing the field as a separate domain ofapplied computing. The research was triggered by the opportuni-ties offered by the development of computing technologies, ratherthan by any explicit real life demand or industrial need [107]. Therewere some remarkablemilestone results in this first period of timesuch as: (i) demonstration of the Sketchpad system by Suther-land in 1963 (which made the first step towards interactive sys-tems) [108], (ii) publication of Bézier in 1962 on the mathematical


representation of a family of curves that is named after him nowa-days, (iii) presentation of the UNISURF system by Bézier in 1968,(iv) holding the first CAD conference in 1964, (v) organizing the au-tomotive design conference by Bezier in 1971, and (vi) starting ofthe first conference on computer aided geometric design in 1974 inUtah. Themain issue for research and developmentwas facilitationof engineering numerical computation and electronic graphical vi-sualizationby the then available premature hardware and softwaretechnologies. In addition, intense research started towards inter-active data input and output (e.g. vector and raster CRT with lightpen), and towards computer-controlled electromechanical graph-ical peripherals (e.g. drum and flat-bed pen plotters), which wereconsidered prerequisites for computer aided drawing. There wasan international research community established by the end of thisperiod [109].

3.3. Consolidation and diversification

The second phase of evolution happened roughly between1971 and 1982. This brought about the consolidation of CAD asa self-standing research and development field [110]. The con-centrated research efforts led not only to enhancement of capa-bilities, but also to a diversification of the considered applicationdomains (mechanical, electronic, architecture, etc.) and supportedphases of product development. This diversification triggered anarticulation of the CAD functionalities. It gave floor to standard(cross-domain) functions such as computer aided drawing, free-form curve/surfacemodeling, wireframe, solid and boundarymod-eling, assembly modeling, finite element analysis, as well as toapplication domain-specific functions and domain-oriented im-plementations of standard functions, such as computer aidedprocess planning, and computer aided manufacturing [111]. Themajor change in terms of the underpinning computing technolo-gies was that researchers shifted their attentions to interactiveworkstations. The need of the industry for CAD systems has rapidlyincreased, in particular in the high-tech industries [112]. The pa-per of Tornincasa and Di Monaco gives a concise but very in-sightful survey of the philosophy and the ways of developing CADsystems, including some milestone development until 2010 [113].In the field of electronic CAD, the concept of CAD framework wasintroduced with the goal of reducing the time and cost needed todevelop or modify a CAD system according to the needs of its usersand to support the interoperation of dissimilar systems [114]. Atthe end of this second phase, the specific focus (geometry inducedalgorithms, methods and tools), the mainstream activities, and theapplication domains of computer aided design have been identi-fied [115].

3.4. Integration and networking

Lasting approximately from 1982 until 1996, a third periodstarted with an intense diversification of the CAD tools, meth-ods and systems. Several CSG and B-rep solid modelers and, lateron, parametric and associative solid modelers have been devel-oped [116]. At the same time, the necessity of making efforts tointegrate models, technologies, activities and representations alsoemerged [117]. In fact, it was triggered by the growing need ofthe high-tech industry for integrated computer aided design sys-tems [118]. The industrial CAD system developers and softwarehouses wanted to offer higher efficiency to their customers, whowanted to achieve interoperation, standardization, homogeneityand effectiveness in their daily processes. With respect to thecomputational support of CAD software packages, a major influ-ence came from the appearance of personal computing and dig-ital networks. These lend themselves to the advancement from

self-contained CAD workstations to personal computer-based (re-motely) cooperating CAD workplaces. Within-system integrationwas mainly concerned with: (i) database level, (ii) modeling level,and (iii) system interface level integration, whereas between-system integration addressed the issues of: (iv) standardized dataexchange between systems, and (v) interoperation of dissimilarsystems [119]. Graphical and geometric kernels have been pro-posed for standardization, and data transfer specifications havebeen introduced [120]. Among the large number of efforts towardsbetween-system data/model exchange, the development of theInitial Graphics Exchange Specification (IGES) [121,122] and Stan-dard for the Exchange of Product Model Data (STEP) enjoyed thelargest support from the industry [123–125]. The technical oppor-tunities of wired computer networking gave an impetus to theabove mentioned research and development efforts. Towards theend of the period, a product life-cycle oriented thinking becamedominant with the intention of placing CAD in a product lifecy-cle management (PLM) environment. The experiences with inte-gration of life-cycle phases and activities pointed at the need formethodological integration. This triggered the research in and thedevelopment of the concept of form and application features, andled to techniques such as parametric design, feature-based design,and feature recognition [126]. As a result, the development streamof CAD became interwovenwith the development streams of threeother technologies, namely:

• computer aided engineering, that dealt with numerical calcula-tions based on artifact and process modeling;

• computer aided process planning, that focused on planning ofmanufacturing processes, and

• computer aidedmanufacturing, that concentrated on providinginformation for computer numerical control of machine tools[127].

Though developers of commercialized mechanical and architec-tural CAD systems achieved significant progress withmodel-basedintegration, Broy et al. reported on a limited everyday use ofmodel-based approaches in the automotive and aircraft industriesand argued that the enablers provided by various engineering en-vironments were only ad-hoc chains of models [128]. On the otherhand, Kalay referred to advanced computer aided design as a newmedia of computer aided architectural design [129]. Interestingly,the concept of intelligent CAD also emerged in this period, but itwas not supported by concrete industrial need, and its develop-ment was hindered by the insufficient maturity of the theoreticalfundamentals and the technological resources.

3.5. Virtualization and collaboration

Perhaps the terms ‘virtualization’ and ‘collaboration’ summa-rize best what has happened in the fourth phase of CAD de-velopment that lasted approximately from 1996 until 2005. Thesophistication of the tools and techniques of mechanical, archi-tectural and electronic CAD system, with three-dimensional geo-metric and structural modeling in their core, contributed to a wideindustrial proliferation of these systems [130]. Improvements havebeen achieved, for instance, in feature-based modeling, freeformsurface modeling, assembly modeling, and product lifecycle man-agement. According to Asanowicz, we may talk about mature CADonly from the end of the 1990s [131]. For instance, history-basedCAD systemswere developed,whichwere able to record the chainsof construction actions, and to capture the intent of the designs bystoring and processing the relationships between the entities usedfor modeling. Interestingly, the concept of history-based modelingwas challenged by a 3D geometry (and assembly) modeling tech-nique, called direct modeling, which could be learnt fast and easyby designers, as opposed to mastering parametric and constraintbasedmodeling, whichwas time consuming and needed expertise.


Fig. 5. The domains and flows of computer aided product development.

However, from the perspective of evolution, the emerging newtechnologies, e.g.: (i) internet-based collaboration technologies,(ii) high-end scientific visualization, (iii) immersive and desktopvirtual and augmented reality technologies, and (iv) semantic soft-ware technologies have made much larger effects on CAD and re-lated activities [132]. PC-based virtual reality (VR) has proved itspotential to improve visualization of complex mechanical assem-blies, high-tech products, buildings, plants and other installations,contrary to the fact that its implementation in the industry hasyet to reach maturity. Immersive VR systems were showed to bebeneficial at post-processing and visualization of the results of en-gineering analyses and simulations [133]. From the mid-1990s,academic research in collaborative design methods, tools and sys-tems has been intensified, and this resulted in both off-line andon-line collaborative CAD systems. The former systems were ableto share the results of the modeling or design process, while thelatter systems were able to share data instantly. Because of the of-fered benefits, on-line collaborative systems soon received moreattention in research. Various agent based technologies have beenconsidered in order to increase both the semantic level and au-tomation of system collaboration [134]. With the inclusion of vir-tual engineering and rapid prototyping technologies, computersupport of product design and engineering could extend from themental domain of humans through the virtual domains createdby computers to the physical domain [135]. This way, it couldcover inspiration, conceptualization, realization and experiencing[Fig. 5].

3.6. Permeation into new domains

It seems that in the last period, namely from 2006 until today,the evolution of CADhas reached the ceiling set by traditional com-puting technologies [136]. In the light of the literature it can besaid that this period is bringing in methodological enhancements

in certain new application domains, rather than brand newcomputing technologies [137]. For instance, various reverse en-gineering (RE) approached were proposed based on image-basedreconstruction or direct three-dimensional (3D) scanning. RE wassupported by the development of various 3D object search, recog-nition and retrieval techniques. Based on the literature, four newrapidly-growing application domains can be identified: (i) bio-physical CAD (including medical and dental CAD), (ii) molecular-CAD (including pharmaceutical CAD), (iii) micro- and nanoCAD,and (iv) VLSI-CAD. Bio-CAD focuses on capturing biological, bio-physical, and biochemical properties for modeling, design, andfabrication of complex tissue substitutes for biomedical applica-tions, but it also extents to biomimetic design, analysis and simu-lation [109]. For instance, as an early attempt, Mörmann proposeda system for restoring posterior teeth by bonded ceramic inlays us-ing an in-office computer aided design and manufacturing systemin a single appointment [138].Molecular-CAD systems are comple-ments of computational chemistry packages, to facilitate design-ingmolecular structures in full atomic detail and providing controlformolecularmanufacturing [139]. Nano-CAD integrates the initial3D nanostructures with the materials properties to build 3D geo-metrical models. Following the actual fabrication, the performanceof the nano-structures are experimentally studied and comparedwith the predictions of the nano-CAD simulators. In each of thesefields computing is applied to geometry-relatedmodeling, analysisand simulation of artifacts and processes. VLSI-CAD systems applyartificial intelligence techniques to handle the complexities and toautomate the logical and physical design of large-scale integrateddigital circuits.

3.7. How about the Journal of Computer-Aided Design?

It is worthy to note that these shifts have been followed bythe changes of the thematic focus of the papers submitted to


the Journal of Computer-Aided Design and the number of paperspublished concerning the above mentioned topics. The journal, asthe first international peer-reviewed journals established in thisfield, has successfully created a forum for presenting the latesttheories, algorithms, systems, and applications. Later on, in theposition of a highly-cited high-impactmedia, it has also influencedthe orientation of academic research. Over the years, it markedthe boundaries of the domain of interest and contributed to thearticulation and development of the discipline. However, over theyears, it wentwell beyondwhat the original aim, namely computeraided drafting, was.

In the fourth period of development, on the basis of a robustgeometric and structural modeling, the Journal of Computer-Aided Design spanned over and interconnected all stages ofa design process from concept creation to manufacture andbeyond. The research and development fields currently consideredrelevant for the journal are: (i) foundational theories, frameworks,methodologies, and standards, (ii) geometric and topologicalmethods for shape and solidmodeling, (iii) structural, material andphysical modeling, (iv) virtual reality and prototyping methods,(v) advanced support of manufacturing and downstream activitiesof product realization, (vi) user interfaces, system interfaces andsystem interoperability, (vii) knowledge-intensive technologiesfor design, (viii) design databases, knowledge repositories, objectlibraries and retrieval, (ix) modeling and design of multi-scaleobjects and systems, (x) specific applications and significantbenchmarks of computer aided design. Now, in the fifth phase ofdevelopment, the Journal of Computer-Aided Design is reportingon the results of application of geometric and structural modelingin a large number of maturing application fields.

4. Attainments in ubiquitous CAD tools and systems

4.1. On two different interpretations of ubiquity in the context of CAD

As explained above, ubiquitous computing is about equippingeveryday things in the real world with information processingpower. In this section we try to cast light on three issues, namelyon (i) the impact of ubiquitous computing on the methodologicalfoundations of computer aided design, (ii) the novel functionalitiesproposed for CAD tools and systems, and (iii) the current state ofart of ubiquitous design support [140]. Before doing this, however,it may be useful to deal with the two prevailing interpretations of‘ubiquity’ in the context of computer aided design.

In the first broad interpretation, ubiquity refers to the trendthat CAD moves out of the hands of specialists and becomes aubiquitous asset of designing. Computer aided design is ubiqui-tous in the design industry and is used to design all things fromgarment through electronic circuits to complex systems. From an-other viewpoint, ubiquity of CAD is reflected by the use of com-puter aided geometric design methods and algorithms in othergeometry-intensive fields, namely, in computer aided engineer-ing, computer aided process planning, and computer aided man-ufacturing. Model-based design and development has been a defacto standard of working in many industries. Over the years,three-dimensional artifactmodeling penetrated into the advertise-ment and entertainment industries. Reverse engineering is nowa method of choice in archeological reconstruction, and feature-based object retrieval is becoming a commodity on the secondgeneration web. The appearance of tablet computers gave a newimpetus to screen-based sketching, but its main application do-mains remained to be styling, artistic imaging, and conceptual de-sign. It is also widely used by non-designers nowadays [141].

In the second narrower interpretation, ubiquity denotes themain promise of ubiquitous computing, namely, that it offers datacollection and communication, modeling and representation, and

computing and reasoning means and services anywhere, anytime,and in any context. A ubiquitous CAD environment is conceivedas the result of augmenting CAD systems with mobile and em-bedded computing, and wireless networking and communicationresources in an integral manner. The objective is to provide perva-sive computing functionality and large-scale mobility. In principle,a ubiquitous CAD environment may involve all resources of cur-rent collaborative design environments and can extend themwithmany novel functions. Furthermore, they are supposed to be uti-lizable in many branches of designing and in many stages of a de-sign process, from ideation, through concept creation, to detaileddesign, and beyond [142]. However, as showed by our survey andinquiries, both the efforts towards the development of ubiquitousdesign enablers (environments, systems, or tools), and the adop-tion of the development results in practical processes are laggingbehind the level that can be assumed after fifty years of existenceof the discipline of computer aided design and themore than thirtyyears of existence of the theory and practice of ubiquitous comput-ing. Below we try to find some general reasons and a defendableexplanation for this situation. Procedurally, we will considerachievements in development of supporting methodologies, spe-cific environments and systems, tasks related tools, and other ini-tiatives.

4.2. The impact of ubiquitous computing on the methodologicalfoundations of CAD

Let us start with some typical proposals for methodologi-cal foundations of the development and operation of ubiquitousdesign systems. Robertson and Radcliffe, examined the ways acomputational environment may influence the ability of design-ing creatively [143]. Their case study identified four phenomenathat influence the impact of CAD tools on creative problem solv-ing in engineering design. They are: (i) enhanced visualization andcommunication, (ii) premature fixation, (iii) circumscribed think-ing, and (iv) bounded ideation. Each of these can be correlatedwiththe interactionwithdesign systems.Ndiwalana andMcCrickard ar-gued that the classic interface design processes should be changedto help designers to envision and design ‘‘better’’ systems inter-faces [144]. They suggested to consider: (i) early design factors (re-quirements analysis), (ii) community factors (conceptual design),(iii) system design factors (system architecting), and (iv) usagefactors (deployment and evaluation). Landay and Borriello pro-posed ubiquitous computing design patterns that help solve dif-ficult problems by reusing prior design knowledge, and offer aneffective way to communicate solutions to ubiquitous comput-ing design problems [145]. Resembling use scenarios, the designpatterns are named as context-sensitive I/O, physical–virtual asso-ciations, global data, proxies for devices, follow-me display, appro-priate levels of attention, and anticipation. These patterns expresseither user interface aspects, or system aspects, or both. Kärkkäi-nen and Laarni proposed design guidelines to support designingwebsites for small display screens such are typical in PDAs [146].They sorted the guidelines into: (i) software and hardware, (ii) con-tent and organization, and (iii) aesthetics and layout categories.Other researchers formulated design principles to support design-ing ubiquitous applications [147,148].

Horváth et al. reported on the results of a study that: (i) ana-lyzed the current results and trends of ubiquitous technology de-velopment, (ii) identified various design-enabling functions thatcan be provided by ubiquitous technologies, and (iii) tried to form avision about the possiblemanifestation of future ubiquitous designsupport environments [149]. As novel ubiquitous CAD functionali-ties they proposed (i) sensor-based collecting of object and processinformation, (ii) exploration and gathering repository information,(iii) conducting operative design research remotely, (iv) data col-lection through products, (v) capturing and synthesizing of context


information, (vi) stimulation ideation on spot, (vii)multi-modal in-spiration of creative conceptualization, (viii) content adaptation toalternative devices, (ix) providing computing services on demand,(x) ad hoc networking with arbitrary information appliances, (xi)(collective) learning on demand (factual data, know how, designskills, design tools and methods), and (xii) information miningfrom verbal communication. They concluded that follow up in-vestigations were needed to further articulate the full range ofthe identified major functions, to operationalize these functionali-ties based on appropriate mobile communication and ubiquitouscomputing technologies, to adapt the functionalities and imple-mentations to real life application cases and practical applicationscenarios, and to study the impacts on designers, products and pro-cesses.

4.3. Ubiquitous design environments and tools

In general, ubiquitous design enabling environments receivedmuch less attention than ambient living and working environ-ments, apparently with the exception of one area. Van Doorn andHorváth studied possible use scenarios and technological plat-forms for digital design studios of the future [150]. Jeng and Lee ar-gued that the current approach to developing electronics-orienteddesign environments was fundamentally defective with regardto supporting multi-person multimodal design interactions [151].They proposed a ubiquitous computing environment, which can beconsidered as a media-rich design studio of the future. More thana decade ago, the concept of ‘living laboratory’ was introduced inwhich researchersmay study ubiquitous technologies in home set-tings and develop context-aware technological and interaction so-lutions [152].

The idea of ubiquitous design tools (UDTs) emerged within theCAD research community almost thirty years ago. The objectiveof developing UDTs is augmenting human abilities variously, de-pending on the nature and context of the tasks. Potential func-tionalities such as (i) multi-location telepresence, (ii) distributedmodel sharing for mobiles, (iii) content transformation for mo-biles, (iv) design context generation, and (v) network-based repos-itories have been considered. It has been conceived that someof the UDTs used in design enabling environments feature fixedlocation, or are remotely accessible through wireless networks(e.g. printers). Another part of them is moving with designersas portable, embedded, wearable and transferable devices, andfeature ad hoc connectivity. These not only offer new ways forinformation seeking (i.e. for aggregation, processing and presen-tation of design information), but also enable alternative ways ofcompleting design activities. The affordances ofwired andwirelesssignal- and data-transfer, and communication and network man-agement were also considered. With a view to the intense interac-tion with humans, a comprehensive analysis and modeling of theusers was found to be important [153]. As influential algorithmdevelopment issues, network-oriented concise 3D visualizations(e.g., HTTP, VRML, X3D, MPEG-4, OpenHSF and Java3D), and 3Dstreaming technologies (e.g., topological mesh simplification, ver-tex decimation, edge contraction, vertex clustering) and mesh re-finement (e.g., multi-resolutionmesh, progressive split) have beenstudied. UDTs that design engineers used in their everyday workinfluenced their ability of solving engineering problems creativelyin both positive and negative ways. Recently, Dow et al. speculatedabout the next generation design tools, considering external rep-resentations used in ubiquitous computing design [154].

4.4. Multi-location co-development using CAD

Co-development of products by designers at different geo-graphical locations was one of the first challenges that received

significant attention from researchers. Both methodological(concurrency, multi-disciplinary, procedural) and technological(modeling, computing and system architecting) proposals werepublished [155]. Supporting remote, cooperation of designers andother stakeholders emerged as a prominent field of using ubiqui-tous computing. In this context various concepts were introducedand scrutinized. The issues of reproducing presence in various cir-cumstances have been widely addressed, also considering virtualreality technologies [156]. It was considered to be important tosupport creative collaborativework and collaboration enabling en-vironments. Among others, Li et al. and Fuh and Li recently pub-lished surveys on the state of the art of collaborative CAD [157,158].Current collaborative design systems integrate knowledge of mul-tiple domains, namely: design theories andmethodologies, knowl-edge management, cognitive psychology, sociology, and computerscience. The tools proposed to support collaborative work spreadover a wide functional domain. Just to mention a few instances,Ouyang et al. developed a distributed collaborative CAD systemusing web services [159]. Tang and Minneman proposed a videointerface for collaborative drawing [160]. Tay presented collabo-rative design software for MEMS development [161]. Kao and Linproposed a collaborative CAD/CAM system [162]. Brown et al. pre-sented aweb-enabled virtual repository for supporting distributedautomotive component development [163]. Since the beginning ofthe 2000’s, language based interaction was used to support collab-orative browsing and search. Han et al. proposed a framework formulti-device collaborative Web browsing, which enables multipleusers to participate in the same browsing session using resourcelimited devices, such as a wireless PDA, and to benefit from themultimedia capabilities of other devices in the vicinity [164]. Chenet al. described a collaborative design environment that includesmultiple CAD systems [165]. Feijó et al. claimed that the prob-lems developers are facing at the development of distributed CADsystems require solutions based on concepts such as emergenceand reactivity, and on online algorithms. Therefore, they proposedextended constraints graphs as online algorithms, which supportemergence in a network of reactive agents [166].

The proliferation of ubiquitous computing based design toolsand systems shows a unique picture. One would expect ubiqui-tous CAD technologies to penetrate first into mechanical or ar-chitectural design (as computer aided design did in the 1960s).Conversely, ubiquitous CAD has become prevalent in the construc-tion industry. For instance, using mobile computing for informa-tion management and communication is a central topic for ICTapplication in this industry [167]. This can be explained by thefact that design in the construction industry is sensitive to site andprocess information [168]. According to Ahsan et al., the great-est benefit of ubiquitous computing in construction sites is thatit enables timely collection of information and knowledge duringthe building process and this can positively influences the decisionmaking processes [169]. Reborlj et al. proposed a mobile comput-ing approach to enhance information collection and distributionin construction processes [170]. Oh et al. presented an interestingapplication of a PDA in teaching a pendant program for a mobileshipbuilding welding robot [171].

4.5. Information and knowledge management

As the ability to query the company’s distributed knowledgebase is important, Kelley analyzed a number of aspects of Web-centric product data management [172]. Sivanathan et al. de-veloped an application of ubiquitous multimodal synchronousdata capture in CAD [173]. Cooperation with co-workers is of agrowing importance. Baresi et al. argued that designers need tomove across organizational boundaries and collaboratewith others


within and outside their own organization [58]. Videoconferenc-ing on fixed network infrastructure is still the standard form, butmulti-media conferencing on mobile devices is the scenario of thefuture. Goldin et al. reported on a NASA project, which establisheda truly-multidisciplinary design environment, called ‘intelligentsynthesis environment’, whose five major components are: (i) hu-man-centered computing, (ii) infrastructure for distributed collab-oration, (iii) rapid synthesis and simulation tools, (iv) life cycleintegration and validation, and (v) cultural change in both the en-gineering and science creative processes [174]. The environment isintended to link scientists, design teams, manufacturers, suppliers,and consultants who participate in themission synthesis as well asin the creation and operation of the aerospace system.

Interestingly, the appearance of ubiquitous enablers did not re-sult in fading away of the traditional technological solutions. In thebuilding industry, traditional large size blue prints and construc-tion plans (generally printed on 24 by 36 in size papers to providethe needed level of detailing and easy readability) retained theirplace in the daily practice. Subcontractors usually need these plans,not only the digital documentation. Therefore, architects and engi-neers use CAD for high power drafting to provide the builders withprints of the design. Anumba et al. identified seven facets of com-munication within construction projects, namely, communicationbetween: (i) intra-disciplinary CAE (computer aided engineering)tools, (ii) each project teammember and their design tools, (iii) de-sign team members, (iv) each discipline and the common projectmodel, (v) the project team and third parties, (vi) inter-disciplinaryCAE tools, and (vii) across the stages in the project life-cycle [156].Jadid and Idress discussed the role of mobile computing and infor-mation technology in civil engineering construction projects [175].Many new ideas have been formulated about future enablers inthe field of computer aided architectural design [30]. One of themis the idea of self-organizing contents, which is stimulated by theneed to over-bridge the differences that exist in terms of the dataprocessing and storage, the display and visualization capabilities ofvarious fix-placed and portable devices. Self-organizing contentsare complemented with algorithms that are able to recognize theoperating characteristics (such as screen sizes, display resolutionsand data transfer speed) of various devices and adapts the contentsaccordingly with the objective to provide the best experience andworking possibility for the end-users.

Though not all ubiquitous computing applications are of a largescale, there are various compliance, complexity and scale issuesrelated to many smart environments. Coroama et al. reported ona project that overviewed the blessings and perils of ubiquitousenvironments, based on various ubiquitous computing scenar-ios [176]. Some researchers presented concepts for light-weightinfrastructure andmiddleware for pervasive computing [177,178].Cook and Das discussed issues concerning the implementation ofpervasive computing at scale [179]. They identified subfields forpervasive computing at scale such as (i) scaling models of indi-vidual and group behavior, (ii) scaling pervasive computing de-vices, (iii) scaling pervasive computing applications, (iv) scalingthrough cloud computing, and (v) scaling through energy analysisand harvesting. Banavar and Bernstein argued that developmentsin ubiquitous design support will require fundamental advances insemantic modeling, context-aware software infrastructure, appli-cation modeling and tools, and user experience validation [180].Other researchers addressed the issues of integrating resources onlarge-scale, the emergence and effects of large-scale use, and pro-cessing large amounts of data.

5. On the involvement of ubiquitous computing in computeraided design

Based on the results of the overview presented in Section 2,we can state that ubiquitous computing creates new potentials

for CAD in the following dimensions: (i) proactive ambientenvironment, (ii) multi-form seeking for information, (iii) flexiblynetworked communication, (iv) omnipresent access to computing,(v) smartly behaving tools, and (vi) direct brain interfaces. At thesame time, the literature shows some sort of ‘virgin land’ as muchas the development of dedicated tools is concerned. Apart fromthe tools developed by virtual and augmented reality researchers(which often has only limited overlap with ubiquitous designsupport tools per se), just a limited number of correlated researchresults have been published. This hints at the fact that applicationof ubiquitous technologies in design support systems and asspecific design tools is lagging behind their application in generalproducts, systems and services. What are the reasons of thissituation and what can we expect for the near and further future?Can we state in the context of design enabling that ubiquitouscomputing has broken its promise to be everywhere?Or, is it betterto think of ubiquitous computer aided design as a Sleeping Beauty,which can be expected to wake up when the ‘prince’ will arrive?

First, let us consider the first question! Did ubiquitous comput-ing indeed break its promise to be everywhere in the formof UDTs?Our study suggests that the answer is yes. But, what are the rea-sons? There are many of them. If we consider the development ofthe CAD functionality and the development of the computing tech-nologies simultaneously, thenwe can observe two things. First, thefunctional spectrum of advanced computer aided design did notextend significantly in the last three stages of its evolution. Themainstream (or) kernel activities remained to be based on geomet-ric or structural modeling and representations. Many of the tech-nologies discussed in the second chapter are not related to theseat all, or do not have too much to do with them. As discussed, thenumber of functions thatmay expect interest outside the academicworld proved to be limited. The literature does not indicate any in-tense activity in this direction.

Second, we have to consider the strategy of the market leadersin CAD system development. In this context we can observe simi-larity with the situation in the automotive industry. The productsof both the leading automobile developers and the leading CAD de-velopers are very similar in terms of their scope, have comparablefunctionalities, and strugglewith the sameunresolved issues. Theirthinking is also similar in terms of their development strategies.The industrial CAD system developers have become somewhat re-luctant to consider radical changes and to extend the CAD envi-ronments with new technologies. Though improvement has beenachieved with regards to interfacing, connectivity, transparencyand integration of the commercialized systems, nowadays only‘face-lifts’ are being introduced in terms of their geometric mod-eling kernels. Apparently, speech and gesture based interfaces didnot and will not be able to penetrate into commercial systems intheir current forms, apart from those augmenting virtual realitysystems, where they play a crucial role [181]. Touch screen basedgeometric input is still not able to cope with the speed and preci-sion of mouse based input. According to many experts, businessprocess innovation is the current focus of the research and de-velopment of the main CAD developers. Industrial end-users alsoprefer incremental developments and improvements, rather thanradical innovations and abrupt changes. For instance, they performa large part of the communication using traditional fix networkedwired or wireless communication, rather than ad hoc communi-cation means. Though this hears as a philosophical issue, the nextparadigm of computer aided design is not known at this moment.

Thirdly, we have to consider the silent battle of digital com-puting-related or -induced technologies. As discussed by Geels andSmit there are many future images that do not come true be-cause they are based on too simplistic conceptualization of tech-nological developments and their impact on society. They call theattention to the importance of the dynamic co-evolution of tech-nological opportunities and the application demands [182]. This is


the basis of our reasoning in the context of ubiquitous computing.Parallel with the emergence and proliferation of ubiquitous com-puting, several other technologies started their life cycles. In thelast two decades, ubiquitous computing technologies had to com-pete with other kinds of computational technologies, such as high-capacity computing, high-speed networking, immersive virtualreality, knowledge ontologies, smart software agents, mobile com-munication, etc., which could have a much stronger influence onthe development of computer aided design methods and systems.In combination with the rather conservative and conventional in-dustrial practice of CAD system development and application, thismay explain why the ubiquitous computing revolution remainedweak in computer aided design. The literature clearly informs usabout the fact that application of ubiquitous technologies did notlead to radically new functionalities that could have been exploitedby the concerned industries. Consequently, it seems to be possi-ble that computer aided design simply steps over the paradigmof ubiquitous computing and expects new functionalities fromthe emerging new computing paradigms, such as brain–computerinterfacing, cyber–physical computing, biological computing, orquantum computing.

Let us now elaborate on the secondly mentioned question!Can we look at ubiquitous computer aided design as the Sleep-ing Beauty,1 who is enchanted to sleep for hundred years and towake up only when a king-son asks her to do so? In other words,can it be expected that, after the decay of the early hype, a nextwave of ubiquitous computing comes and gives a new techno-logical impetus to computer aided design? We are rather skep-tic about this happening for two reasons. First, it does not seemto be the case that a next wave of ubiquitous computing wouldcurrently be formed. Second, digital computing is presently ad-vancing under the influence of a next paradigm that has beencalled cyber–physical computing. Furthermore, other computingparadigms such as biological computing and quantum computingare already around the corner. Cyber–physical computing embedsmany technological features of ubiquitous computing, but it alsosignificantly extends the technological and functional capabilities.By saying this, we do not want to say that cyber–physical comput-ing will have any bigger potential to enable next generation com-puter aided design, than ubiquitous had. Interestingly, there areno publications on any relationship of cyber–physical computingand computer aided design. We must be careful. Lee argued thatcyber–physical computing is ‘pushing hard at the frontiers of engi-neering knowledge, putting severe stress on the abstractions andtechniques that have proven so effective in the separate spaces ofcyber systems (information and computing technology) and phys-ical systems (the rest of engineering)’ [183].

6. Concluding propositions and future research opportunities

Ubiquitous computing emerged at the beginning of the 1980sand its main assumption is that computing can be available any-where, anytime and any context and in anything due to tech-nological developments, new affordances, and societal demand.

1 Though everybody knows the classic fairytale of the Sleeping Beauty, in a nutshell,one variant of the story is: A fairy, who had not been invited to the christening of along-wished-for new born princess of the king, became angry and placed the princessunder an enchantment as her gift: the princess would prick her hand on a spindle anddie. Another fairy managed to change the curse of the evil fairy from dying to falling intoa deep sleep for 100 years and be awoken by a handsome prince. One day the princesshurt her finger by the spinningwheels and the cursewas fulfilled. The good fairy foresawthat the princess would be alone when she woke up and so put everyone in the castle tosleep. A hundred years passed, and a prince came from a far off land. He found the oldcastle in the surrounding forest during a hunting expedition and the beautiful sleepingprincess inside the castle. The enchantment came to an end, and the princess woke uptogether with the castle folk. The prince and princess fell in love, got married, and livedhappily throughout their live.

This idea has been introduced and exploited successfully in manyapplication fields over the years. In the past, whenever a new com-putational paradigm appeared, it was supposed to bring aboutdisruptive innovations. However, our research informed us, ubiq-uitous computing has not managed to revolutionize the method-ologies and the systems of computer aided design, though manyresearchers studied the affordances and the possible applicationsof ubiquitous technologies. In general, ubiquitous computing so farhas had only a limited impact on computer aided design, exceptfor some specific application area. Certain new functionalities andnovel tools have been developed by researchers at the academia,but they have not been integrated into commercial systems andindustrial best practices.

In this paper we tried to find some rational explanations forthis situation. It is hoped that the selected and analyzed paperscould provide sufficient underpinning of the below propositions.However, it has to bementioned that, as every survey, this one canbe seen as incomplete. The selection of the papers considered isbased on subjective decisions, but wewere also constrained by theobvious page limitation. Our conclusions concerning the currentsituation and future opportunities can be summarized as follows:• In most of the application fields, the geometric and structure

modeling capabilities of computer aided design are primarilyexploited. The presently consolidating new application fieldsof computer aided design, such as bio-CAD, nano-CAD, andsystems-CAD, rely on themodeling functions of CAD, Therefore,penetration of ubiquitous computing in these applicationsremained insignificant.

• However, in applications where real time information seekingand design communication play an important role, for instancein the construction industry, much significant penetration andadvancement could be observed.

• In addition to the limited match of the technological af-fordances of ubiquitous computing and the functional ex-tendibility of computer aided design, a probable reason of themoderate proliferation is that ubiquitous computing technolo-gies had in the last two decades to compete with other kinds ofcomputational technologies, such as high-capacity computing,high-speed networking, immersive virtual reality, knowledgeontologies, smart software agents, mobile communication, etc.These had a stronger influence on the development of computeraided design methods and systems.

• The industrial developers and influential users of commercialCAD systems seem to prefer incremental development to radi-cal innovations. Since they favor consolidated technologies, thefast emerging and rapidly changing ubiquitous computing tech-nologies could not get through their firewalls. The conservativeand conventionalist industrial CAD practice also contributed tothe slightness and localized nature of the ubiquitous computingrevolution.

• The literature clearly indicates that even the academic re-searchers did not intellectualize and prototype radically newubiquitous CAD functionalities. Based on the present applica-tion domains, unexplored functional opportunities seem to belimited. Consequently, it is very probable that computer aideddesign simply steps over the paradigm of ubiquitous comput-ing. Fairy tales typically do not apply in real life.

• What seems to be interesting for near future research is abroader investigation and exploitation of brain–computer in-terfacing technologies and applications. It may introduce somenew functions and novelways of interactingwithin the physicalworld, as well as with virtual objects in the cyber world.

• Multidisciplinary research groups may also put on their re-search agendas and make the first steps in exploring the affor-dances of the currently emerging new computing paradigms,such as cyber–physical computing, biological computing, orquantum computing.


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ubiquitous computer aided design: a broken promise or a sleeping beauty?

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