energy efficient intelligent street lighting system using traffic-adaptive control

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Energy-Efficient Intelligent Street Lighting System Using

Traffic-Adaptive Control Abstract:

Lighting, both indoor and outdoor, consumes a substantial amount of energy,

making improved efficiency a significant challenge. A promising approach to

address outdoor lighting is the smart control of public lighting. Smart lighting

using electronically controlled light-emitting diode (LED) lights for adaptable

illumination and monitoring are bring used to achieve energy efficient system.

However, the traffic engineering integrated with smart control for energy

optimization has not been used widely. In this work, a novel concept of traffic-

flow-based smart (LED) street lighting for energy optimization is proposed. The

developed smart grid architecture based system uses low power ZigBee mesh

network to provide maximum energy efficiency in response to adaptive traffic on

the road. Moreover, the scalable wireless network of smart LED lights offers

improved reliability, reduced cost and more user satisfaction.

Existing system:

Presently disaster management is done through seismometers around the area

obtain immediate earthquake information for reducing damage. It may be enough

to obtain general condition of earthquake over area, but too small to collect

information with fine granularity such as data of each building for effective rescue

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operation or damage control. There are several preceding researches whose

objectives are close to ours proposes an earthquake information system using

laptop PCs which equip accelerometers Some of another research groups uses

mobile smart devices.

Disadvantage:

As a result, the existing proposal gets very few data which have been helpful

in finding disaster management.

In other systems the internet is used as primary and only communication

channel. This leads to breakdown in local internet will makes the break in

communication.

Block Diagram:





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Proposed system: This system consists of two parts. One is the central database server that collects

and stores information from distributed sensor terminal, and then, provides them to

clients via the Internet. The other is a sensor network which is formed by numerous

sensor probes that are placed in buildings. The sensor probe consists of gas sensor,

temperature sensor and accelerometer to gather the required parameters. The

accelerometer is used to find seismic action, the gas sensor to find any leakage of

harmful or flammable gas and the temperature sensor to find temperature around

the probe. The system forms a wireless network to transfer information of each





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probe up to the central server. We employed ZigBee wireless technology for this

network as mentioned in the previous section.

Advantages:

These 3 sensors are available as convenient modules in the market and easily

connectable to MCU.

The critical levels of the hazardous gases such as LPG in the buildings have

been indicated through alerting unit.

The system successfully detected the primary appearances of earthquake.

Conclusion:

The huge amount of energy and cost associated with lighting applications has

driven the need to address both budget issues and environmental concerns. In this

work, a smart, efficient LED lighting system is proposed and implemented,

exploiting the unique opportunities of both LED and sensor and control

technologies. Unlike previous works, a probabilistic approach followed by a

statistical analysis of varying-time-based traffic has been considered to implement

an optimal system. The system combines the additional benefits of LED

technology, such as the use of a wireless control system for traffic-based dimming





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to conserve energy, at a savings of 80 % over previously-installed metal halide

bulbs.

Reference :

[1] J. Crowther, C. Herzig, G. Feller, “The time is right for connected public

lighting within smart cities”, IBSG., Cisco System, San Jose, CA, Oct. 2012.

[2] International Energy Agency (IEA), “Light’s labour’s lost, policies for energy

efficient lighting,” Paris, 2006.

[3] European Expertise Centre (EPEC), “Energy efficient street lighting,” 2013.

[4] Koninklijke Philips Electronics, “Road lighting, feel safe on roads,” August,

2013.

[5] D. Caicedo and A.Pandharipande, “Distributed illumination control with local

sensing and actuation in networked lighting system,” IEEE Sensor J., vol. 13, no.

3, pp 1092-1104 , March. 2013.

[6] M. Magno, T. plonelli, l. benini, E. popovivi, “A low cost, highly scalable

wireless sensor network solution to achieve smart LED light control for green

buildings,” IEEE Sensor J., vol. 15, no. 5, pp 2963-2973, May. 2015.

[7] S.D.T Kelly, N.K. Suryadevara, S.C. Mukhopahyay, “Towards the

implementation of IoT for environment condition and monitoring in homes,” IEEE

Sensor J., vol. 13, no. 10, pp 3846-3853, Oct. 2013.



energy efficient intelligent street lighting system using traffic-adaptive control

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