optimization of a wireless sensor network-based smart

Research ArticleOptimization of a Wireless Sensor Network-Based Smart ElderlyLocation Management System

Biying Wang,1 Dingzhuang Chen ,2 and Liangpeng Xu3

1School of Public Affairs, Fujian Jiangxia University, Fuzhou, Fujian 350108, China2School of Business and Management, Xiamen Huaxia University, Xiamen, Fujian 361024, China3Transmission Network Consulting and Design Institute, Fujian Post and Telecommunications Planning and Design Institute Co.,Ltd., Fuzhou, Fujian 350001, China

Correspondence should be addressed to Dingzhuang Chen; [email protected]

Received 12 October 2021; Revised 28 October 2021; Accepted 1 November 2021; Published 17 November 2021

Academic Editor: Guolong Shi

Copyright © 2021 Biying Wang et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

In this paper, wireless sensors are used to design and build a location management system for smart aging, and the optimization ofthis system is analysed. The function and structure of the positioning system are designed and implemented. Next, the systemcommissioning process and field implementation results are summarized and analysed to guarantee the reliability and integrityof the system. Finally, the system requirements and implementation are integrated to realize the basic requirements of the IoT-based elderly positioning management system and reserve the interface for later expansion. Finally, the system excellence andfunctional usability tested through unit testing as well as comprehensive testing. In this paper, a theoretical analysis of theprediction algorithm is carried out for the disease prediction module in the health monitoring software of the smart seniorcare system. To improve the accuracy of the prediction, the traditional BP neural network algorithm is optimized using DSevidence theory, thus fusing multiple sets of prediction results obtained from the BP neural network into a more accurate setof data, and the performance of the algorithm before and after the improvement is compared. The IoT-based home healthmanagement for the elderly starts from the health service demand of the elderly, explains the basic concept of IoT technologyand home health management for the elderly, and analyses the feasibility of home health management for the elderly and theadvantages of IoT technology in-home health management for the elderly; through the field research, the IoT-based homehealth management platform for the elderly is carried out from three aspects of users, business, and technology. The designcovers the platform architecture and functional modules of the IoT-based senior home health management platform, whichcan solve the problem that the elderly can spend a comfortable life in their old age without going home.

1. Introduction

With the rapid development of IoT, big data, and wearabletechnology, intelligence and automation provide a new direc-tion for solving the elderly problem, and the concept of smartaging is increasingly understood. With the development ofthe network as well as wireless sensor technology, IoT tech-nology is playing an increasingly important role in people’sdaily life [1]. The Internet of Things (IoT) refers to the inte-gration of various information sensing devices and systems,such as sensor networks, bar codes, RF tag reading devices,GPS, QR code devices, and other “thing-to-thing”-basedcommunication modes- (M2M-) based short-range wireless

self-organizing network system, through various access net-works and the Internet to form a huge intelligent network[2]. Through IoT technology, we can combine intelligentsensing and recognition technology with artificial intelli-gence technology, thus breaking the traditional elderly caremindset by interacting various sensor devices with mobileInternet networks, allowing young people to understand thedaily activities of the elderly in real-time through the net-work, and to be notified in time when the elderly have abnor-mal conditions, to give them precise care [3]. The direction ofmedical care, spiritual comfort, life entertainment, etc. haschanged, becoming increasingly diversified and diversified,which has led to a series of elderly care including health care

HindawiJournal of SensorsVolume 2021, Article ID 2760746, 12 pageshttps://doi.org/10.1155/2021/2760746

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products, medical institutions, elderly health care institu-tions, elderly physical examinations, and elderly tourism. Inindustry development, this new type of elderly care systemthat combines the Internet of Things and artificial intelli-gence is known as the Smart Senior Care System. This systemnot only enables the elderly to receive timely and accuratecare in nursing homes but also improves the living experi-ence of the elderly in nursing homes, fully satisfying theneeds of the elderly for the services and management pro-vided by nursing homes, and allowing young people to restassured that they will be placed in nursing homes for the restof their lives. The number of the elderly population is gradu-ally growing, the development and progress of economic andtechnological level, the improvement of quality of life, whichmakes the demand of the elderly for health and old age grad-ually expand from the previous single demand for health careservices to the direction of health care, spiritual comfort, liveentertainment and so on, more and more diversified anddiverse, thus driving the development of a series of seniorcare industries including health care products, medical insti-tutions, health care institutions for the elderly, and medicalcheck-ups for the elderly. This has led to the developmentof a series of senior care industries, including health careproducts, medical institutions, health care institutions forthe elderly, medical check-ups for the elderly, and tourismfor the elderly [4]. In addition, the health needs of the elderlyare also subdivided into different levels according to theirphysical health, economic status, living environment, etc.The diversified development of the health needs of the elderlyhas put forward more health service needs for the elderly tothe society, and the demand gap for the elderly is expanding,and how to age healthily has become a key concern of societytoday.

The continuous development of healthy aging, coupledwith the expansion of intelligent technology into the fieldof senior care, has further raised the expectations of theelderly for senior care services, and the smart senior care ser-vice platform is the core part of smart senior care, whichcontrols the connection between senior care service supplyand senior care demand, and is the current form of smartsenior care realization strongly advocated by the govern-ment [5]. The smart senior care service platform usesadvanced Internet of Things, communication, and remotetechnology to provide senior care services for the elderly. Itis based on individual families and communities and pro-vides real-time monitoring services for the elderly throughmonitoring devices, external wearable devices, and so on,to make the daily life of the elderly safer and worry-free, orprovide timely assistance in case of emergency. The develop-ment of the smart elderly service platform makes old peo-ple’s later life safer and healthier, fully reflecting thesignificance of the development of healthy aging.

Based on the development history and development sta-tus of the smart senior care service platform, the develop-ment stages of the smart senior care service platform andthe development of policy, technology, and demand changesunder each stage are analysed to provide optimization sug-gestions for the construction of the smart senior care serviceplatform. Studying the health needs of the elderly makes

society understand the necessity of the elderly problem,accelerates the efficiency of the government’s elderly service,and can also drive the further development of the elderlyindustry. With the increase of the proportion of the elderly,the elderly and their families have greater consumptionpotential, and it is the intelligent elderly care that stimulatesthe consumption potential of the elderly and their families,which is conducive to expanding domestic demand, stimu-lating the innovative vitality of elderly care enterprises, pro-moting the further optimization and upgrading of intelligentelderly care products and equipment, and accelerating thesustainable and healthy development of elderly care serviceindustry and high-tech industry. At the same time, optimi-zation suggestions are made on how to better build a smartsenior care service platform according to the health needsof the elderly. From the perspective of healthy aging theoryand supply and demand theory, the first consideration ofthe smart senior care service platform is to meet the healthysenior care needs of the elderly, and from the perspective ofhuman-computer interaction, the development of the smartsenior care service platform is to find more effective seniorcare methods so that the elderly can continue to realize theirvalue, that is to say, to match and analyse the smart seniorcare platform, the health needs of the elderly and the smartsenior care products, and to use the relevant supply anddemand matching analysis, using theories related to supplyand demand matching to conduct research and analysis.The thesis uses the theory of healthy aging, the theory ofhierarchy of needs theory as the theoretical support and useshuman-computer interaction, supply and demand match-ing, and other related theories to better build the smartsenior care service platform and enriches the connotationand extension of these theories.

2. Status of Research

In terms of technology, foreign research in informationmanagement of elderly institutions also started early, andthe relevant mature systems are generally higher than thosein China in terms of performance, functions, and expansionneeds. Foreign elderly management systems have adopted alot of IoT technologies, such as the Inter-Home in Europeand the United States and the IT machine care system inJapan, all of which are designed to achieve all-round moni-toring of the elderly through real-time monitoring of allaspects of their daily lives and health data [6]. At the sametime, multilevel care services are realized for different cate-gories of elderly people, such as those with dementia, disabil-ity, or emotional impairment. However, a reasonableresponse to the elderly problem is another opportunity fornational economic transformation and industrial modelupgrading. As a new industry, the elderly care industry hasgreat potential [7]. We can fully learn from the successfulexperience in the elderly care system in Asia, Japan, Europe,and the United States developed countries, combine ournational conditions and industry direction, and build asocialist elderly care security system with Chinese character-istics [8]. The development of the ZigBee-based elderly caresystem is a large practical innovation based on existing

2 Journal of Sensors

management systems and applications. The traditionalinformation management system is organically combinedwith a wireless self-assembly network, and the resourcesare reasonably allocated to provide diversified, multilevel,and highly reliable positioning management services follow-ing China’s current stage of elderly care design requirements[9]. The implementation of the system can significantlyimprove the standard of elderly care services and reducethe cost of social elderly care and provide more reliable, safe,and swift care and health monitoring services for the elderly.The design and application of elderly care systems based onZigBee wireless network positioning technology have greatapplication and social value in both academic and practicalaspects and have great academic research significance inelderly care industry exploration and service innovation [10].

In the study, an intelligent apartment is envisaged inwhich the elderly does not need any caregiver and have fullautonomy and privacy [11]. Sensors, as well as communica-tion and location facilities, are installed in such an apart-ment incorporating IoT technology. When the elderly needto go out, the sensors in the room will detect and alert thecaregivers; when the elderly have an accident, the sensorson the floor will also detect and react accordingly; whenthe elderly need to take medication on time, the sensorsinstalled on the elderly will alert the elderly and report themedication taken to the caregivers through the communica-tion chip. Most of the nursing homes do not have profes-sionally trained personnel or the quality of the industry ismixed, and most nursing homes are constrained by eco-nomic costs and space, so it is difficult to achieve one-to-one elderly care staff [12]. Therefore, intelligent manage-ment of nursing homes is inevitable. There are already rele-vant research units and enterprises in China developingintelligent nursing home management systems, which detectthe physiological status of the elderly through various func-tional sensors [13]. Given this, an intelligent IoT nursinghome management solution combining Bluetooth Meshtechnology and sensor technology is the goal of this design.

The objectives of smart elderly care services are pro-posed to make full use of primary health care, reduce thewaste of resources in health care facilities, and facilitateaccess to elderly care services in familiar places of residence.Using the rooting theory to study the living environmentand convenient facilities of the elderly, it is pointed out thatincreasingly elderly people prefer to live in places with carecommunities to improve their safety and quality of life intheir later years. Foreign studies generally agree that themost dominant elderly care service in the future is smartcommunity elderly care. A framework for a dependency-based smart elderly care service system has been proposed,using this framework to assess the elderly to determine theright time to serve them and provide them with humane ser-vices. The Singapore government highly advocates diversi-fied smart elderly care services, and to ensure the smoothimplementation of smart elderly care services, a series oflaws and regulations have been formulated based on a highdegree of community autonomy to provide policy protectionfor the development of smart elderly care.

3. Optimization Analysis of Smart AgingLocation Management System with WirelessSensor Network

3.1. Design of Smart Aging Location Management Systemwith Wireless Sensor Network. A nursing home is a placewith complete facilities mainly for the elderly, providingthem with comprehensive accommodation, entertainment,catering, and medical services. Different levels of nursinghomes in different places generally use management systemsdeveloped for their business characteristics to help themmanage their services, so that they can better protect thesafety, physical, and mental health of the elderly, the reason-able deployment of various resources in the home, as well asto ensure the level of care services and work efficiency, to doa good job of elderly care services. Intelligent positioning callmanagement system consists of system server, system termi-nal, hub, wireless gateway, wireless locator and wireless loca-tor card, and other equipment [14]. The direction of medicalcare, spiritual comfort, life entertainment, etc. has changed,becoming increasingly diversified and diversified, whichhas led to a series of elderly care including health care prod-ucts, medical institutions, elderly health care institutions,elderly physical examinations, and elderly tourism. In indus-try development, the system is designed with a B/S structure,and the network composition includes two parts: basicEthernet and wireless Internet of Things. The basic Ethernetis used to connect the system server and each system termi-nal, as well as to reach out to other systems, using the exist-ing network lines of the elderly care centre. The wireless IoTis used to connect each wireless positioning device and is thebase network of the intelligent positioning help system. Thedevices that make up this network use the internationallyaccepted ZigBee wireless communication protocol. The pro-tocol has the characteristics of short distance, low powerconsumption, low cost, strong anti-interference, supportfor a variety of network topologies, automatic networking,large capacity of node devices, signal collision detection,safety, and reliability, etc. In the intelligent positioning callmanagement system, the wireless communication protocolused by each wireless positioning device is the completeimplementation of the ZigBee wireless communication pro-tocol. Based on these features, the wireless locator can beinstalled and deployed without additional wiring and canbe automatically networked by taking power nearby; thewireless locator card can work reliably for several yearsunder the battery-powered model.

net j = 〠n

i=1wijxj + ai,

hj = f 〠n

i=1wijxj + ai

!:

ð1Þ

The collection, storage, and use of data from the Intelli-gent Location Call Management System are implementedthrough a database server [15]. The database server is the

3Journal of Sensors

provider of all web-based data services. The data sourcesmainly involve wireless positioning device information,building layout information of the elderly care centre, asso-ciation information of the elderly and positioning cards,basic staff information, basic system information of systemusers, role permissions and other system information, andsystem parameter information. The data source of the posi-tioning call management system mostly collected by the sys-tem itself, and only when it is linked with the videomonitoring system and access control system, it is necessaryto obtain part of the data from these systems, and the way toobtain it can be operated by directly accessing each other’sdata source or using each other’s communication pipes.When the mobile alarm moves within the network, the sig-nal strength of the communication between the mobilealarm and each positioning base station changes with thedistance between them. Since there is a certain correspon-dence between the signal strength and the distance and thelocation coordinates of each positioning base station areknown, the location of the mobile alarm can be calculatedafter knowing the signal strength between the mobile alarmand multiple positioning base stations. The topology of thepositioning call system is shown in Figure 1.

Each positioning algorithm has its characteristics; thereis no best algorithm, only the most suitable algorithmcombined with the actual field needs and working envi-ronment. Referring to the introduction of positioning algo-rithms and the research area of this paper, the mostsuitable positioning algorithm and deployment methodare selected by combining the environmental characteris-tics and functional requirements of the senior care indus-try. Both the positioning system and the algorithm requirean ideal wireless communication environment and reliablenetwork node devices.

The real environment is often complex, and there areproblems such as node failure or excessive distance or anglemeasurement errors caused by node hardware limitations, sothe positioning system and algorithm must be highly fault-tolerant and adaptive, capable of correcting errors throughautomatic adjustment or reconstruction, fault managementof the wireless sensor network, and reducing the impact ofvarious errors [16].

This makes the daily life of the elderly safer and moreworry-free or provides timely assistance in the event of anemergency. The development of the smart elderly care ser-vice platform makes the old age life of the elderly saferand healthier and fully reflects the development signifi-cance of healthy aging. The management function designof the intelligent positioning helps the system fully con-sider the actual management business characteristics ofelderly institutions, combines the management mode andbusiness processes, and develops a system function archi-tecture scheme that can meet the business needs. At thesame time, it considers the development trend of informa-tion technology and fully considers the business expansioninterface. The system is custom-developed for elderly insti-tutions. User rights management, part of the data dictio-nary, and basic information of the elderly can be sharedwith the intelligent business management system.

yk = 〠n

i=1wijhj + bi,

E = 12〠

M

k=1e3k:

ð2Þ

Video surveillance linkage is used when a call for helpis generated; the system tries to obtain the signals ofnearby available video surveillance probes based on thelocation of this wireless locator card and then displaysthem simultaneously to increase the amount of informa-tion. The related management operations include locationinformation entry of the video probe, association withthe wireless locator, interception display of the video sig-nal, and automatic control of the advanced probe, suchas rotation, zoom in, and zoom out. Access control linkageis used to collaboratively obtain control information ofnearby access control as needed when the call for help isgenerated. In addition, when the access control in the gen-eration of card swipe operation, intelligent positioninghelp system can be based on the location information ofthe access control to calibrate the wireless positioning cardlocation information. Related management operationsinclude access control location information entry, associa-tion with the wireless locator, and data interaction withthe access control system.

bel Að Þ = 〠B∈A

m Bð Þ∗−E 12〠M

k=1e3k: ð3Þ

Commonly used data preprocessing strategies aredivided into four main categories: data clarity, data inte-gration, data transformation, and data statute. Amongthem, the role of data cleansing is to remove irrelevantdata, duplicate data, handle outliers, handle missing values,and smooth noisy data from the original data. The role ofdata integration is to merge multiple data sources andstore the merged data in a consistent data warehouse. Datatransformation is mainly for the appropriate processing ofdata that is not in a standardized format and converting itto a uniform format to accommodate algorithms that havedifferent requirements for data sources. Data statute is toreduce the size of a larger data set but at the same timeensure the integrity of the data set. Data statutes can effec-tively reduce the impact of invalid and anomalous data onmodel building, improve the accuracy of modelling andreply to reduce the time required for modelling, and canreduce the cost of storing data.

K = 〠A∩B≠0

m1 Að Þm2 Bð Þ: ð4Þ

For the elderly health model building, we choose touse a supervised machine learning algorithm combinedwith the daily location data of the elderly to build theelderly health status, prediction model. Since the super-vised machine learning algorithm requires expected output


labels, in practice, we need to have specialized medicalpersonnel to make basic assessments of the health statusof the elderly in nursing homes daily, such as “healthy,”“cold,” and use the assessment data as the correspondinglabels for the training of the elderly health state predictionmodel. After that, the health state prediction model can beused to predict the health state of the elderly in combina-tion with the location data of the elderly. As a result, theworkload of health care workers in nursing homes canbe effectively reduced. When the smart elderly systemdetects the abnormal state of the elderly, it can notifythe health care personnel in time through the app, to pro-vide timely and accurate care services for the elderly andprevent problems before they occur, as shown in Figure 2.

In the nursing home management, needs to increase thehardware facility mainly include the wristband, the informa-tion read-write, the data transmitter, the computer, and theserver. Among them, the wristband is worn by the oldman and records the corresponding information, the infor-mation read-write carries on the read-out of this informa-tion, the data transmitter carries on the centralizedcollection to the information read-write in its range andtransmits to the corresponding computer, to carry on thedaily information implementation record and the informa-tion inquiry and so on the operation. And the server carrieson the storage to the information, for the external networkinquiry, and so on. The wristband is an important devicefor information collection and transmission for the elderly;a well-functioning wristband should include the followingfunctions. The wristband writes the information of theelderly into the book to carry out the identification of the

elderly information. The wristband has a built-in chip,which can be used to locate the information accuratelythrough GPS so that the location information of the elderlycan be checked easily and the real-time management of theelderly can be realized [17]. The wireless Internet of Thingsis used to connect various wireless positioning devices and isthe basic network of the intelligent positioning help system.The devices that make up the network use the internationalZigBee wireless communication protocol. Through thewristband to the elderly to carry out relevant informationtips, including activity tips and daily service information,the first thing is to determine what is the goal of system tun-ing, if the application has now met the demand, there is noneed to do system tuning; after all, without going througha system process, it is impossible to determine whether thesystem performance, operability, and other indicators ofadjustment done tuned the performance, whether it didnot cause other problems in the application, so it is veryimportant to determine the goal of tuning.

First, we have information on the daily habits and casehistory of the elderly. Knowing the past habits of the elderlyis equivalent to predicting the emergence of diseases inadvance. Secondly, a risk assessment made regarding thecurrent health of the elderly. The type and controllabilityof the disease are analysed so that solutions can be analysedsooner. Some controllable risk factors can be controlledthrough simple matters such as exercise and meals, andhealth that is not a controllable risk can be regulated throughinterventions to reduce the tendency of its aggravation, con-trol the deterioration of the disease, and achieve furtherimprovement. The essence of the intervention is to monitor

Wireless location gateway Wireless location gateway

Wireless location gatewayWireless location gateway

Wireless location gateway

Ethernet transmission

Wireless transmission path

Wireless transmission pathWireless transmission path

Wireless transmission path Wireless transmission path


Wireless locator










Elder

Figure 1: Location call system topology.

5Journal of Sensors

and check the occurrence of diseases through continuousinterventions, and to guide them through education andawareness while abandoning the approach of enforcement.After the four stages of health management are completed,the cycle of health management starts from the first levelof physical examination, which is repeated to slowly changethe bad habits of the elderly and further improve the stan-dard of living of the elderly in managing their health athome.

3.2. Optimal Analysis and Design of the Intelligent ElderlyPositioning Management System. The main types of mobilecommunication devices are special mobile communicationgateways and mobile phones for the elderly; however, themobile terminal watch-type health manager can provideusers with timely heart rate detection services while beingable to conduct automatic search and data transmission, safeand synchronous monitoring of the elderly’s real-time phys-ical health, warning of abnormalities in the elderly whileproviding professional guidance on the physical healthassessment of the elderly, the home health. It can also pro-vide professional guidance on the health assessment of theelderly and interflow with the database of the home healthmanagement centre to improve the plan of the elderly’s dif-ferent dishes and physical health interventions. Somedevices in the home such as blood glucose meters and lipidmeters can be connected to smartphones through their Blue-tooth function for public body sign data collection. Part ofthe data obtained from these systems can be obtained bydirectly accessing the data source of the other party or usingthe communication channel of the other party to operate.When the mobile alarm device moves within the network,the signal strength of the communication between themobile alarm device and each positioning base station willchange as the distance between them changes. They can col-lect and track information such as signs about the family aswell as different individuals at any time and place and createa health profile with this information [18]. The devices canautomatically alert in case of abnormalities. Also, as the

needs of the customer base are constantly changing,smartphone-related sensory features are being developedand innovated.

The staff of the health management platform for theelderly is kind enough to prepare a health file for each mem-ber as well as the emergency contact information of the plat-form, and this file corresponds to the informationmanagement of the corresponding health terminal. For theelderly to achieve at-home use can use the correspondinghealth management terminal system, such as blood glucosemeter, weight meter, blood pressure meter, and other devicesto transmit personal data, to detect the physiological param-eters of the elderly information, and will be through the rel-evant devices such as smart TV, computer, and mobilephone, into the health management platform. Whether theelderly is outside or at home, whether they are using smart-phones or the newly developed watch type manager, theycan realize the transmission of their physical health data eas-ily with the push of a button, and when the data is transmit-ted to the health management platform, the managementcentre will be able to always monitor the health of theelderly. After receiving the information from variousdevices, the senior home health management platform willrecord the information of the elderly in normal conditioninto the file, but there are also some out of normal value,which requires professional medical personnel to determinewhether the abnormal value is dangerous. For some infor-mation identified as health abnormalities, the system willautomatically start calling the seats and handing the infor-mation to the professionals. The elderly person is contactedin time to ask about the situation or their family membersare contacted and sent to the hospital for urgent healthchecks. The senior home health management platform candevelop good health plans based on the long-term healthinformation of the elderly, provide the best quality healthservices for the elderly, and hold healthy community activi-ties from time to time. The health management centre canalso use the positioning system to grasp the specific situationof the elderly in real-time, to make it more convenient to

Presentation layer

Functional layer

Web server

Database

Server

Browser

Ask

Ask

Ask

Ask

Elderlyhealthmodel

building

Algorithmcombined

Elderlyhealthstatus

Expectedoutput

Specializedmedical

personnel

Assessment data as the corresponding label for the

training of the elderly health state

Predicitionmodel

Dailylocation

data

Supervisemachine

Worker innursing homes

Effectivelyreduced

Smart elderlysystem

State of the elderly

Health carepersonnel

The health state prediction model canbe used to predict health state of

the elderly in combination with thelocation data of the elderly

Response

Response

Response

Response

Figure 2: Architecture of the B/S model.


serve the elderly and create a safe, comfortable, and healthyliving environment. Various hospitals have partnership withthe management platform, and they can make appointmentsonline to see a doctor, and even remote treatment and inqui-ries, making complete preparation for the physical and men-tal health of the elderly [19]. If the elderly urgently needs tobe rescued, the senior home health management platformcan provide doctors with the most comprehensive healthinformation about the elderly, as well as relevant files,increasing the success rate of successful resuscitation, asshown in Figure 3.

Based on IoT technology, the application framework ofelderly home health management carriers is divided intoseveral levels, data integration application, data integrationlayer, data collection layer, etc., while it can be divided intothree levels due to the features of the function. The main taskis data collection, which includes device collection and dataentry of various smart devices. Through various systemssuch as websites, mobile phones, and home appliances, thecollection of physical health data of the elderly is completed.And these data will be collected and stored centrally in thehealth management work platform. The data constructionlayer mainly includes the data sharing and business collabo-ration between the second- and third-level medical institu-tions and community medical service centres about thephysical health records of the elderly. This application layeris mainly a portal facing the elderly residents to realize theintegration of health records and monitoring data of theelderly, mainly including chronic disease prevention andassessment, health education, prediction and trend analysis,health monitoring, and early warning.

The data processing layer includes a basic informationdatabase, GIS database, and business sharing database, toprovide data support for the application layer. The data pro-cessing collects complex health big data about the elderlythrough the platform, stores this huge and scattered infor-mation in the system’s database, and mines this data infor-mation to provide data analysis for active matchingservices for the elderly. Real-time management of the elderlywas realized. Relevant information prompts for the elderlythrough the wristband, including activity prompts and dailyservice information. The first is to determine what the goalof system tuning is. If the application now meets the require-ments, there is no need to do system tuning. The data pro-cessing layer not only collects and analyses informationabout the elderly but also provides data on medical institu-tion information and medical staff information. The dataprocessing centre can also process data based on mutualfeedback between the elderly and service providers and pro-vide better services for both parties. Big data mining of theplatform can provide a clear direction for smart elderly ser-vices. The changing health needs of the elderly are in linewith the economic level and social development, and theseneeds include low-level survival needs as well as high-levelself-actualization needs. Demand drives supply, thus drivingthe development of a series of elderly care industries such asmedical institutions, health care products, and smart appli-ances. And with the continuous progress of the times andthe continuous innovation of technology, more demands

for elderly health services will be put forward to society,and the smart elderly service platform will also change withthe changing health needs of the elderly, as shown inFigure 4.

With the improvement of living standards, the demandfor elderly education and mental health has become moreobvious, while most of the services provided by the platformare on care needs, and there is a gap between the supply ofservices and the demand for services. Improving the servicecontent of the smart senior care service platform from thehealth needs of the elderly is a problem that must be consid-ered for the better development of the smart senior care ser-vice platform [20]. At the same time, the various systems ofsmart senior care are complex, each system is independentof each other, lacking effective communication and connec-tion, and resources not integrated, which is not conducive tothe integrated management of the platform of smart seniorcare services, and the scheduling optimization and effectiveuse of senior care service resources. The recognition of theelderly population to the wisdom senior care service prod-ucts also remains at a low stage, and a good interactionmodel cannot be formed yet. The services provided by thesmart senior care service platform are mainly reflected inthe passive response to the health needs of the elderly, whilethe intelligent control technology is used to carry out remotereal-time monitoring of the daily actions, living conditions,physical functions, and other data of the elderly analysethe service needs of the elderly and actively provide servicesfor the elderly, and the intelligent level of smart senior care isnot high.

4. Results and Analysis

4.1. Performance of Smart Aging Location ManagementSystem with Wireless Sensor Network. With age, the elderlywill experience physiological decline, and their ability toaccept and adapt to the surrounding environment and infor-mation decreases, which will also be accompanied by slowreaction and poor acceptance. The platform should be builtaccording to the different health needs of different elderlypeople, integrate the elderly service resources, and connectmedical institutions and service organizations for the smartelderly service. The construction of the smart senior care ser-vice platform is generally combined with senior care serviceinstitutions and medical institutions, and in order to attractmore resources, the platform should also be modifiedaccording to the requirements of service institutions andmedical institutions to make it its own smart senior care ser-vice platform, so the smart senior care service platformshould be improved in terms of software facilities and hard-ware facilities, not only need to build a more intelligent andsafe platform, develop suitable senior. Therefore, the smartsenior care service platform should be improved in termsof software facilities and hardware facilities, not only to builda smarter and safer platform, develop wearable devices suit-able for the elderly but also to renovate and upgrade thesmart senior care service items and systems, so that the ser-vice items and systems are flexible and elastic, in addition toimproving the professionalism of senior care services,

7Journal of Sensors

providing personalized and customized services and healthmanagement plans for the elderly to meet their health needsto the maximum extent, as shown in Figure 5.

The sharing of resources for the elderly is reflected in thefollowing: firstly, the sharing of resources for service person-nel, who should serve every elderly person equally, and theelderly should also enjoy the services equally. Medicalresources can play an important role in the services for theelderly, and the elderly can physically examine using medical

testing equipment, and the doctor will then make a goodrecord of the data so that there is no differentiation in thetreatment of the elderly. Finally, the data sharing of all plat-forms, including the existing information platform of healthinformation and elderly service information, to establish astandardized interoperable information common data-sharing system, so that all kinds of elderly service institu-tions, medical institutions can data sharing, these informa-tion data can be effective to the development, to provide

Electronic medical record Condition registration Health education

Medical records

Smartphone data inputInspection Report

Manual input of test dataForecast and trend analysisMedical imaging

Medical records Health testing data collection

Patient index

Expertknowledge

base

Automatic collection of smartdevices

Chronic disease preventionand evaluation

Health monitoring and earlywarning

Follow-up record

Output

Figure 3: Framework of the physical health management work platform for older persons at home.

Health checkupFamily care

Key alarmPsychologicalcounseling

Humanistic care

Life care Health management Safety monitoring

Purchasing agent Life entertainment Remote monitoring Customized service

Basic care

Rehabilitation

FeedbackServices

Figure 4: Service content of the smart senior care service platform.


data support for the elderly services, to promote the sharingand integration of health and elderly big data. There are alsodocking elderly users who have signed up with family doc-tors, family doctors because they have been with the elderlyfor a long time, understand the habits and physical condi-tion of the elderly, have professionalism and target, and willanalyse the health needs of the elderly and the elderly ser-vices needed from a professional perspective. We are alsoworking to expand the coverage of basic public services,improve the quality of life of the elderly in need, and developcommunity-based elderly care services, such as elderly carehomes, which combine elderly care and day-care, and pro-vide elderly care services to the elderly in the surroundingcommunities to expand the scope of radiation. The develop-ment of smart senior care service platforms has changedfrom “point clustering” to “surface dispersal,” which meansthat the development of smart senior care service platformshas changed from focusing on hardware investment in thepast to focusing more on “software services” nowadays. Thismeans that the development of the smart senior care serviceplatform has changed from focusing on hardware invest-ment in the past to focusing more on “software services” tocontinuously meet the multilevel health and senior care ser-vice needs of the elderly, as shown in Figure 6.

In the case of using only acceleration as the basis for falljudgment detection, the fall judgment is more accurate, butthe judgment miscalculation rate is higher for daily actions,including walking, sitting, and lying down, so a more rigor-ous judgment basis needs to be introduced. The angularvelocity value is used for joint judgment to improve theaccuracy of the system, while in the actual judgment, theangular velocity only takes the value of the z-axis direction.Through the experimental analysis, the two actions of walk-ing and sitting down, the SVM may produce larger values,but at this time the z-axis angular velocity is relatively smallwithin 40°/s, and the lying down action is the opposite resultSVM value is smaller, the angular velocity reaches 220°/s ormore, while in the actual fall, the human body collides withthe ground SVM and z-axis angular velocity reach the peak

at the same time, respectively, 2.7 g and 227°/s. Therefore,the SVM threshold of the system was finally set to 2.5 gand the z-axis angular velocity threshold was set to 210°/s.

4.2. Systematic Optimization of Aging Positioning Results.The purpose of system user management is to ensure thesecurity of the system, and its functions include doctor usermanagement, elderly user management, personal informa-tion modification and audit management, and user rightsmanagement. Users can only perform other secondary oper-ations after successful login. It is possible to collect and trackthe sign information about the family and different individ-uals at any time and place and establish this informationinto a health file. The device can automatically alarm whenan abnormality occurs. At the same time, as the needs ofcustomer groups are constantly changing, the related per-ception functions of smart phones are also constantly beingdeveloped and innovated. To ensure the authenticity of userinformation, the administrator will have unified assignaccounts after reviewing user applications and has theauthority to modify user information, and only users whohave been approved by the administrator can use the system.The health monitoring module is the core module of thismonitoring software, mainly including two submodules ofreal-time monitoring and history recording. Real-time mon-itoring means that the hardware device uploads the physio-logical data collected from the elderly to the server, and theelderly can view the real-time data by logging into themobile client; history record means that the software showsthe elderly the average value of the daily health data mea-sured within a specified period in the form of lists andcharts. Through the trend changes reflected in the graphs,the elderly can intuitively understand whether their physio-logical data is in a relatively stable range and roughly judgetheir current health status with their actual feelings. In addi-tion, the history also includes the medical examinationrecords and consultation records of the elderly in the

9492908886848280787674727068

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Figure 5: Change in acceleration during a fall.

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Figure 6: Network communication test results.

9Journal of Sensors

community hospital, so that the elderly can have compre-hensive control of their health, as shown in Figure 7.

Testers 1 and 2 experienced positioning jitters whenapproaching 3, 4, and 5. The analysis showed that thereceived RSSI jumped when the bracelet was judging theposition due to factors such as occlusion or interferencefrom indoor personnel. The results of the test met the expec-tations, and the testers were able to suppress the positioningjitter better when they gathered, and the real-time perfor-mance was also guaranteed due to the loose setting of the fil-tering parameters.

The emergency rescue module provides a data anomalyalarm and a one-touch call for help. Abnormal data includes

location data and health data. The abnormal alarm based onlocation data means that the client uses the relevant servicesof Baidu Map to obtain the current location of the elderly,and the system administrator will notify the elderly’s familyin time after receiving the warning message; the abnormalalarm based on health data means that when the measuredphysiological data of the elderly exceeds the normal range;the system will notify the administrator in time and send apush reminder to the elderly’s mobile phone. The one-touch call for help function means that when an elderly per-son encounters an emergency and needs help; he or she willclick the one-touch call for help button and the client willjump directly to the dialling interface of the mobile phone

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Figure 7: Historical positioning data.

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Figure 8: Fall test data.


to contact the previously set emergency contact or the seniorservice centre and request help. The doctor-patient commu-nication module used community elderly and communitydoctors, helping the elderly and doctors to communicatedirectly. Seniors can use the online message function to asktheir doctor about their health, and the doctor will reply baseon the message. In addition to the online message, theelderly can also call the doctor directly for a detailed consul-tation, as shown in Figure 8.

From the waveform, we can see that the waveform iscomplete and recognizable in the stationary state, and theheart rate value can be calculated more accurately; whilethe curve fluctuates more when walking and talking, andbecause it is measuring the wrist, there may be a situationthat the bracelet moves when walking, and the peaks andvalleys cannot be accurately recognized. To solve this prob-lem, by analysing the working principle of heart rate sensorduring the movement of many bracelets with heart rate col-lection function on the market, we adjust the program logicof the bracelet, increase the judgment of acceleration sensordata during heart rate detection, suspend the sensor datacollection if there is a large acceleration fluctuation, delaythe detection time, and wait until the bracelet is in a morestatic situation before heart rate and blood oxygen detectionto reduce unnecessary. This reduces unnecessary data errorsand misjudgement of the management system.

5. Conclusion

In this paper, we studied the key technologies involved in theIoT nursing home management system and determined thetechnical direction; then, we collected existing nursing homemanagement system solutions, fully analysed and under-stood them, summarized the pain points solved in these sys-tems, took the essence of their elderly management andbusiness management, and combined them with the needsof the nursing home management system designed in thispaper to develop the overall design plan, hardware. Theoverall design plan, hardware design plan, and softwaredesign plan are formulated; then, the hardware design andsoftware design and development work are carried out, andthe hardware devices such as hand ring, relay node, andgateway in the system are selected with chip sensors andhardware circuit design, and the Bluetooth Mesh networkcommunication plan, Bluetooth Mesh-based indoor posi-tioning plan, sensor acquisition plan, and management sys-tem upper computer software development plan aredesigned; finally, after the completion of the above hardwaredevices and upper computer software, the system is devel-oped. Finally, after completing the hardware equipmentand the software, the software and hardware testing environ-ments are set up in the actual scenario to test the key tech-nologies in the system: Bluetooth Mesh communication,indoor positioning, heart rate, and oxygen saturation collec-tion and calculation, body temperature collection and calcu-lation, and the elderly fall detection function, and theperformance and error of each test item are analysed indetail with the test data and improvement suggestions andsolutions are given. The construction of the smart elderly

service platform should be based on and solve the currentsituation of the aging problem, and constantly alleviate thecontradiction between the health needs of the elderly andthe shortage of service supply. The smart elderly should beimproved and designed through the overall system of thegovernment, society, and millions of families, and, finally,achieve the goal of smart elderly with effective use ofresources and high efficiency and intelligence. It will relievethe pressure on the elderly, make every family have a betterlife, and make the elderly live a healthier life in their old age.

Data Availability

The data used to support the findings of this study are avail-able from the corresponding author upon request.

Conflicts of Interest

The authors declare that they have no known competingfinancial interests or personal relationships that could haveappeared to influence the work reported in this paper.

Acknowledgments

This work was supported by the Key project of FuzhouSocial Science Fund in 2017, A Study on the Accurate Supplyof Home-based Community Elderly Care Services in FuzhouCity (2017FZB10).

References

[1] D. Perea-Strom, A. Morell, J. Toledo, and L. Acosta, “GNSSintegration in the localization system of an autonomous vehi-cle based on particle weighting,” IEEE Sensors Journal, vol. 20,no. 6, pp. 3314–3323, 2020.

[2] W. Wen, G. Zhang, and L. T. Hsu, “Object-detection-aidedGNSS and its integration with Lidar in highly urbanizedareas,” IEEE Intelligent Transportation Systems Magazine,vol. 12, no. 3, pp. 53–69, 2020.

[3] T. Suzuki, “Time-relative RTK-GNSS: GNSS loop closure inpose graph optimization,” IEEE Robotics and Automation Let-ters, vol. 5, no. 3, pp. 4735–4742, 2020.

[4] T. M. Quack, M. Reiter, and D. Abel, “Digital map generationand localization for vehicles in urban intersections usingLiDAR and GNSS data,” IFAC-PapersOnLine, vol. 50, no. 1,pp. 251–257, 2017.

[5] Y. Li, Z. He, Z. Gao, Y. Zhuang, C. Shi, and N. el-Sheimy,“Toward robust crowdsourcing-based localization: a finger-printing accuracy indicator enhanced wireless/magnetic/iner-tial integration approach,” IEEE Internet of Things Journal,vol. 6, no. 2, pp. 3585–3600, 2019.

[6] G. Soatti, M. Nicoli, N. Garcia, B. Denis, R. Raulefs, andH. Wymeersch, “Implicit cooperative positioning in vehicularnetworks,” IEEE Transactions on Intelligent TransportationSystems, vol. 19, no. 12, pp. 3964–3980, 2018.

[7] C. Wen, Y. Dai, Y. Xia et al., “Toward efficient 3-d coloredmapping in GPS-/GNSS-denied environments,” IEEE Geosci-ence and Remote Sensing Letters, vol. 17, no. 1, pp. 147–151,2020.

[8] G. M. Hoang, B. Denis, J. Härri, and D. Slock, “Fusion bayesi-enne de donnees GNSS, ITS-G5 et IR-UWB pour des

11Journal of Sensors

applications robustes de localisation vehiculaire cooperative,”Comptes Rendus Physique, vol. 20, no. 3, pp. 218–227, 2019.

[9] S. K. Singh, S. Raval, and B. Banerjee, “A robust approach toidentify roof bolts in 3D point cloud data captured from amobile laser scanner,” International Journal of Mining Scienceand Technology, vol. 31, no. 2, pp. 303–312, 2021.

[10] M. Karimi, M. Oelsch, O. Stengel, E. Babaians, andE. Steinbach, “LoLa-SLAM: low-latency LiDAR SLAM usingcontinuous scan slicing,” IEEE Robotics and Automation Let-ters, vol. 6, no. 2, pp. 2248–2255, 2021.

[11] K. Qiu, T. Liu, and S. Shen, “Model-based global localizationfor aerial robots using edge alignment,” IEEE Robotics andAutomation Letters, vol. 2, no. 3, pp. 1256–1263, 2017.

[12] Q. Shi, S. Zhao, X. Cui, M. Lu, and M. Jia, “Anchor self-localization algorithm based on UWB ranging and inertialmeasurements,” Tsinghua Science and Technology, vol. 24,no. 6, pp. 728–737, 2019.

[13] R. Karlsson and F. Gustafsson, “The future of automotivelocalization algorithms: available, reliable, and scalable local-ization: anywhere and anytime,” IEEE Signal Processing Maga-zine, vol. 34, no. 2, pp. 60–69, 2017.

[14] Y. Li, Z. Hu, Z. Li, M. A. Sotelo, and Y. Ma, “Multiscale sitematching for vision-only self-localization of intelligent vehi-cles,” IEEE Intelligent Transportation Systems Magazine,vol. 10, no. 3, pp. 1–183, 2018.

[15] T. H. Nguyen, T. M. Nguyen, and L. Xie, “Range-focusedfusion of camera-IMU-UWB for accurate and drift-reducedlocalization,” IEEE Robotics and Automation Letters, vol. 6,no. 2, pp. 1678–1685, 2021.

[16] Z. Gong, R. Ying, F. Wen, J. Qian, and P. Liu, “Tightly coupledintegration of GNSS and vision SLAM using 10-DoF optimiza-tion on manifold,” IEEE Sensors Journal, vol. 19, no. 24,pp. 12105–12117, 2019.

[17] K. W. Chiang, G. J. Tsai, H. J. Chu, and N. el-Sheimy, “Perfor-mance enhancement of INS/GNSS/refreshed-SLAM integra-tion for acceptable lane-level navigation accuracy,” IEEETransactions on Vehicular Technology, vol. 69, no. 3,pp. 2463–2476, 2020.

[18] G. Vassena and A. Clerici, “Open pit mine 3D mapping by tlsand digital photogrammetry: 3D model update thanks to aslam based approach,” International Archives of the Photo-grammetry, Remote Sensing and Spatial Information Sciences,vol. XLII-2, no. 2, pp. 1145–1148, 2018.

[19] R. Jurevičius, V. Marcinkevičius, and J. Šeibokas, “RobustGNSS-denied localization for UAV using particle filter andvisual odometry,” Machine Vision and Applications, vol. 30,no. 7-8, pp. 1181–1190, 2019.

[20] W. Sun, J. Wang, F. Jin, and Y. Yang, “A quality improvementmethod for 3D laser slam point clouds based on geometricprimitives of the scan scene,” International Journal of RemoteSensing, vol. 42, no. 1, pp. 378–388, 2021.


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