Energy Harvesting Wireless Sensors for Smart Cities
Abstract:
Wireless sensor networks (WSNs), part of the fast emerging Internet of Things will be playing vital role in transforming our lives. Potentially huge number of these sensors will soon be deployed to perform simple to complex tasks such as automatically controlling heat and light in smart homes to guiding autonomous vehicles and missiles. A big challenge in WSN is providing energy. Battery management and maintenance of these sensors can be a prohibitively expensive exercise because of their abundance. Sensors’ performance will deteriorate with the remaining energy level and dead sensor nodes will affect the performance of an entire network, especially in multi-hop networks. Improper battery disposal will also cause environmental pollution and health hazardous in the long run. The energy issue can be alleviated by energy harvesting. The ambience has energy in the forms of light, heat, mechanical vibrations and electromagnetic radiations. This energy has to be collected with appropriate transducers, stored reliably and used for wireless data transmission which is typically happens as bursts. The sporadic and unreliable nature of the energy harvesting process as well as characteristics of electronic elements has to be appropriately modeled to design viable energy harvesting WSN.
EXISTING SYSTEM:
A smart city is a vision for the efficient management of resources such as water, electricity, transport and parking, the lights of roads and the parks, the supervision and monitoring of hospitals and schools, etc [4]. The internet of things (IoT) network is anticipated to be the key for the realization of this kind of smart city [5]. For example, for the efficient use of water resources, the city water management department should be able to access the weather forecast information so that it can hold the process of watering plants based on the rain forecast to save a significant amount of water [6] [7]. Segments of our cities are being infused with technology capable of scavenging energy from the environment, and then using that harnessed power to drive low power communication and sensor technologies. Traffic patterns, pollution monitoring, parking space availability, and utility usage will soon become accessible to citizens in real-time with the combination of embedded sensors and wireless communication being distributed throughout our neighborhoods.
PROPOSED SYSTEM:
In this paper, we present a brief overview of energy harvesting wireless sensors and different sources of energy to be harvested for smart cities. Finally, we report two case studies of energy harvesting using shoe pad and thermal energy. Advances in energy harvesting technologies have led to the possibility of realizing Energy Harvesting – Wireless Sensor Networks (EH-WSNs), making it possible to power wireless embedded devices by small-scale ambient energy. Given the energy-usage profile of a node, energy harvesting techniques could meet partial or all of its energy needs. A widespread and popular technique of energy harvesting is converting solar energy to electrical energy. Solar energy is uncontrollable—the intensity of direct sunlight cannot be controlled—but it is a predictable energy source with daily and seasonal patterns. Other techniques of energy harvesting convert mechanical energy or wind energy to electrical energy. For example, mechanical stress applied to piezo-electric materials, or to a rotating arm connected to a generator, can produce electrical energy.
CONCLUSIONS:
The capability of a wireless sensor node to harvest energy has the potential to simultaneously address the conflicting design goals of lifetime and performance. In this paper, we discussed various aspects of energy harvesting systems. We presented basic concepts of harvesting systems— basic architectures and describe different types of harvestable energy sources. We have reported two case studies for energy harvesting through shoe pad and thermal energy. The method of energy harvesting is one of the major considerations in the design of any self-powered, wireless sensors system. The most common ambient energy sources, which include mechanical vibrations, wind, rotational kinetic energy, and solar and thermal energy, used for wireless sensors systems are briefly overviewed. Currently the energy harvesting equipment is bigger in size and thus, further research is needed to reduce the size of the components for easier integration with tiny sensor nodes. Also, it is financially costly to convert harvested energy into useable power and this challenges its usage in low cost WSN. Considerable research is therefore, necessary to reduce the financial cost while enhancing the conversion efficiency.
REFERENCES:
[1] J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey,” Computer Networks, vol. 52, no. 12, pp. 2292–2330, 2008.
[2] A. Castagnetti, A. Pegatoquet, T. N. Le, and M. Auguin, “A joint dutycycle and transmission power management for energy harvesting WSN,” IEEE Trans. Ind. Informat., vol. 10, no. 2, pp. 928–936, May 2014.
[3] P. Kamalinejad, C. Mahapatra, Z. Sheng, S. Mirabbasi, V.C. Leung, and Y.L. Guan, “Wireless energy harvesting for the internet of things,” IEEE Communications Magazine, vol. 53, no. 6, pp.102-108, 2015.
[4] S. Aslam, N.U. Hasan, J.W. Jang, and K.G. Lee, “Optimized energy harvesting, cluster-head selection and channel allocation for IoTs in smart cities,” Sensors, vol. 16, no. 12, p.2046, 2016.
[5] A. Zanella, N. Bui, A. Castellani, L. Vangelista, and M. Zorzi, “Internet of things for smart cities,”. IEEE Internet Things J. vol. 1, pp. 22–32, 2014.
[6] P. Verma, A. Kumar, N. Rathod, and P. Jain, “Towards an IoT based water management system for a campus,” In Proceedings of the 2015 IEEE First International Smart Cities Conference (ISC2), Guadalajara, Mexico, 25–28 October 2015, pp. 1–6.
[7] A. Gaura, B. Scotneya, G. Parra, and S. McCleana, “Smart city architecture and its applications based on IoT,” Comput. Sci., vol. 52, pp. 1089–1094, 2015.
[8] S. Guo, C, Wang, and Y. Yang, “Joint mobile data gathering and energy provisioning in wireless rechargeable sensor networks,” IEEE Transactions on Mobile Computing, vol. 13, no. 12, pp. 2836–2852, 2014.
[9] S. Sudevalayam and P. Kulkarni, “Energy harvesting sensor nodes: Survey and implications,” IEEE Commun. Surveys Tuts., vol. 13, no. 3, pp. 443–461, Sept. 2011.
[10] A. Kansal, J. Hsu, S. Zahedi, and M. B. Srivastava, “Power management in energy harvesting sensor networks,” Trans. Embedded Computing Systems, vol. 6, no. 4, p. 32, 2007