ABSTRACT
The research work provides an intelligent renewable power irrigation system for protracted and continuous power supply. In Bangladesh, irrigation is one of the most powerful sources, however it is difficult for a single person to monitor continually and on a regular basis. To make this irrigation easier, our system includes certain modifications to the standard irrigation system. A solar panel, a lithium battery, an architectural model, and a system circuit make up the proposed system. The lithium current battery charging control is characterized by hardware rather than software, increasing the system's dependability and stability. It likes to use solar energy whenever there is enough sunlight, when there is ample sunshine, it prefers to use sun's radiation, while the rechargeable battery acts as a backup in case of conditions such as overcast, rain, and night. To completely use solar energy, the system includes a maximum power point tracking (MPPT) controller., and it provides an extraordinarily long life for the lithium battery using an optimal charging approach that reduces the frequency of the battery charge-discharge cycle. This system may be implemented using low-power technology, as a result, it's suitable for Internet of Things wireless sensor nodes deployed outside (IOT).
- Arumugam, G. S., & Ponnuchamy, T. (2015). EE-LEACH: development of energy-efficient LEACH Protocol for data gathering in WSN. EURASIP Journal on Wireless Communications and Networking, 2015(1), 1-9.Google ScholarCross Ref
- Nakas, C., Kandris, D., & Visvardis, G. (2020). Energy efficient routing in wireless sensor networks: a comprehensive survey. Algorithms, 13(3), 72.Google ScholarCross Ref
- Othman, M. F., & Shazali, K. (2012). Wireless sensor network applications: A study in environment monitoring system. Procedia Engineering, 41, 1204-1210.Google ScholarCross Ref
- Pawar, P. P. (2016). Run-Time Management for Multicore Embedded Systems with energy Harvesting (solar energy). International Journal of Management, IT and Engineering, 6(9), 13-22.Google Scholar
- Anastasi, G., Conti, M., Di Francesco, M., & Passarella, A. (2009). Energy conservation in wireless sensor networks: A survey. Ad hoc networks, 7(3), 537-568.Google ScholarDigital Library
- Vullers, R. J., Van Schaijk, R., Visser, H. J., Penders, J., & Van Hoof, C. (2010). Energy harvesting for autonomous wireless sensor networks. IEEE Solid-State Circuits Magazine, 2(2), 29-38.Google Scholar
- Akhtar, F., & Rehmani, M. H. (2015). Energy replenishment using renewable and traditional energy resources for sustainable wireless sensor networks: A review. Renewable and Sustainable Energy Reviews, 45, 769-784.Google ScholarCross Ref
- Boicea, V. A. (2014). Energy storage technologies: The past and the present. Proceedings of the IEEE, 102(11), 1777-1794.Google ScholarCross Ref
- Xu, Z., Li, Z., Holt, C. M., Tan, X., Wang, H., Amirkhiz, B. S., ... & Mitlin, D. (2012). Electrochemical supercapacitor electrodes from sponge-like graphene nanoarchitectures with ultrahigh power density. The journal of physical chemistry letters, 3(20), 2928-2933.Google Scholar
- Waag, W., Käbitz, S., & Sauer, D. U. (2013). Experimental investigation of the lithium-ion battery impedance characteristic at various conditions and aging states and its influence on the application. Applied energy, 102, 885-897.Google Scholar
- Vetter, J., Novák, P., Wagner, M. R., Veit, C., Möller, K. C., Besenhard, J. O., ... & Hammouche, A. (2005). Ageing mechanisms in lithium-ion batteries. Journal of power sources, 147(1-2), 269-281.Google ScholarCross Ref
- Ecker, M., Gerschler, J. B., Vogel, J., Käbitz, S., Hust, F., Dechent, P., & Sauer, D. U. (2012). Development of a lifetime prediction model for lithium-ion batteries based on extended accelerated aging test data. Journal of Power Sources, 215, 248-257.Google ScholarCross Ref
- Jiang, X., Polastre, J., & Culler, D. (2005, April). Perpetual environmentally powered sensor networks. In IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005. (pp. 463-468). IEEE.Google Scholar
- Xiang, Y., & Pasricha, S. (2015). Run-time management for multicore embedded systems with energy harvesting. IEEE Transactions on very large-scale integration (VLSI) Systems, 23(12), 2876-2889.Google ScholarDigital Library
- Dutta, P., Hui, J., Jeong, J., Kim, S., Sharp, C., Taneja, J., ... & Culler, D. (2006, April). Trio: enabling sustainable and scalable outdoor wireless sensor network deployments. In 2006 5th International Conference on Information Processing in Sensor Networks (pp. 407-415). IEEE.Google Scholar
- Sharma, H., Haque, A., & Jaffery, Z. A. (2018, October). An efficient solar energy harvesting system for wireless sensor nodes. In 2018 2nd IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES) (pp. 461-464). IEEE.Google ScholarCross Ref
- Berger, A., Hörmann, L. B., Leitner, C., Oswald, S. B., Priller, P., & Springer, A. (2015, April). Sustainable energy harvesting for robust wireless sensor networks in industrial applications. In 2015 IEEE Sensors Applications Symposium (SAS) (pp. 1-6). IEEE.Google ScholarCross Ref
- Kansara, K., Zaveri, V., Shah, S., Delwadkar, S. and Jani, K., (2015). Sensor based automated irrigation system with IOT: a technical review. International Journal of Computer Science and Information Technologies, 6(6), pp.5331-5333.Google Scholar
- Shekhar, Y., Dagur, E., Mishra, S. and Sankaranarayanan, S., (2017). Intelligent IoT based automated irrigation system. International Journal of Applied Engineering Research, 12(18), pp.7306-7320.Google Scholar
- Rajalakshmi, P. and Mahalakshmi, S.D., (2016, January). IOT based crop-field monitoring and irrigation automation. In 2016 10th International Conference on Intelligent Systems and Control (ISCO) (pp. 1-6). IEEE.Google Scholar
- Khelifa, B., Amel, D., Amel, B., Mohamed, C. and Tarek, B., (2015, July). Smart irrigation using internet of things. In 2015 Fourth International Conference on Future Generation Communication Technology (FGCT) (pp. 1-6). IEEE.Google Scholar
- Muangprathub, J., Boonnam, N., Kajornkasirat, S., Lekbangpong, N., Wanichsombat, A. and Nillaor, P., (2019). IoT and agriculture data analysis for smart farm. Computers and electronics in agriculture, 156, pp.467-474.Google Scholar
- Shah, K., Pawar, S., Prajapati, G., Upadhyay, S. and Hegde, G., (2019). Proposed Automated Plant Watering System Using IoT. Available at SSRN 3360353.Google Scholar
- Dall'Ora, R., Raza, U., Brunelli, D., & Picco, G. P. (2014, September). SensEH: From simulation to deployment of energy harvesting wireless sensor networks. In 39th Annual IEEE Conference on Local Computer Networks Workshops (pp. 566-573). IEEE.Google ScholarCross Ref
- Sharma, V., Mukherji, U., Joseph, V., & Gupta, S. (2010). Optimal energy management policies for energy harvesting sensor nodes. IEEE Transactions on Wireless Communications, 9(4), 1326-1336.Google ScholarDigital Library
- Ramasur, D., & Hancke, G. P. (2012, May). A wind energy harvester for low power wireless sensor networks. In 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings (pp. 2623-2627). IEEE.Google ScholarCross Ref
- Khan, J. A., Qureshi, H. K., & Iqbal, A. (2015). Energy management in wireless sensor networks: A survey. Computers & Electrical Engineering, 41, 159-176.Google ScholarDigital Library
- Yi, G., Guiling, S., Weixiang, L., & Yong, P. (2009, December). Wireless sensor node design based on solar energy supply. In 2009 2nd International Conference on Power Electronics and Intelligent Transportation System (PEITS) (Vol. 3, pp. 203-207). IEEE.Google Scholar
- Naveen, K. V., & Manjunath, S. S. (2011, September). A reliable ultracapacitor based solar energy harvesting system for wireless sensor network enabled intelligent buildings. In 2011 2nd International Conference on Intelligent Agent & Multi-Agent Systems (pp. 20-25). IEEE.Google ScholarCross Ref
- Chuang, W. Y., Lee, C. H., Lin, C. T., Lien, Y. C., & Wu, W. J. (2014, September). Self-sustain wireless sensor module. In 2014 IEEE International Conference on Internet of Things (iThings), and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) (pp. 288-291). IEEE.Google ScholarDigital Library
- Taneja, J., Jeong, J., & Culler, D. (2008, April). Design, modeling, and capacity planning for micro-solar power sensor networks. In 2008 International conference on information processing in sensor networks (ipsn 2008) (pp. 407-418). IEEE.Google ScholarDigital Library
- Madushanki, A.R., Halgamuge, M.N., Wirasagoda, W.S. and Syed, A., (2019). Adoption of the Internet of Things (IoT) in Agriculture and Smart Farming towards Urban Greening: A Review. International Journal of Advanced Computer Science and Applications, 10(4), pp.11-28.Google Scholar
- Saraf, S.B. and Gawali, D.H., (2017, May). IoT based smart irrigation monitoring and controlling system. In 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) (pp. 815-819). IEEE.Google Scholar
- Bhuvaneswari, P. T. V., Balakumar, R., Vaidehi, V., & Balamuralidhar, P. (2009, July). Solar energy harvesting for wireless sensor networks. In 2009 First International Conference on Computational Intelligence, Communication Systems and Networks (pp. 57-61). IEEE.Google Scholar
- Isaacson, M. J., Hollandsworth, R. P., Giampaoli, P. J., Linkowsky, F. A., Salim, A., & Teofilo, V. L. (2000, January). Advanced lithium-ion battery charger. In Fifteenth Annual Battery Conference on Applications and Advances (Cat. No. 00TH8490) (pp. 193-198). IEEE.Google Scholar
- He, H., Xiong, R., Zhang, X., Sun, F., & Fan, J. (2011). State-of-charge estimation of the lithium-ion battery using an adaptive extended Kalman filter based on an improved Thevenin model. IEEE Transactions on vehicular technology, 60(4), 1461-1469.Google ScholarCross Ref
- Takahashi, K., Saitoh, M., Asakura, N., Hibino, T., Sano, M., Fujita, M., & Kifune, K. (2004). Electrochemical properties of lithium manganese oxides with different surface areas for lithium-ion batteries. Journal of power sources, 136(1), 115-121.Google ScholarCross Ref
- Yunjian, L., Xinhai, L., Huajun, G., Zhixing, W., Qiyang, H., Wenjie, P., & Yong, Y. (2009). Electrochemical performance and capacity fading reason of LiMn2O4/graphite batteries stored at room temperature. Journal of Power Sources, 189(1), 721-725.Google ScholarCross Ref
- Li, X., Wu, Y., Li, G., Zeng, Q., & Wang, S. (2010). Development of wireless soil moisture sensor base on solar energy. Transactions of the Chinese Society of Agricultural Engineering, 26(11), 13-18.Google Scholar
- Rodríguez Díaz, E. Camacho Poyato and M. Blanco Pérez, "Evaluation of Water and Energy Use in Pressurized Irrigation Networks in Southern Spain", Journal of Irrigation and Drainage Engineering, vol. 137, no. 10, pp. 644-650, 2011. Available: 10.1061/(asce)ir.1943-4774.0000338.Google Scholar
- Year:2018Google Scholar
- Date:JuneGoogle Scholar
- Copyright Year:2018Google Scholar
- Copyright Statement:rightsretainedGoogle Scholar
- DOI:10.1145/1234567890Google ScholarDigital Library
- RRH: F. SurnameGoogle Scholar
- Price:$15.00Google Scholar
Index Terms
- A Low-Power Wireless Sensor Network for a Smart Irrigation System Powered by Solar Energy
Recommendations
Enhancing the Efficiency of Solar Energy Harvesting System for Wireless Sensor Network Nodes
AbstractTo solve the problem of wireless sensor network (WSN) nodes’ limited battery energy, this study's goal is to provide an effective solar energy harvesting method. Due to their short battery life, WSN nodes have a significant design limitation, so ...
Performance Analysis of Solar Powered Wireless Sensor Network
AbstractWireless sensor network (WSN) is one of the important systems in remote operations that are necessary in defence and industrial applications. Powering these systems is critical in the monitoring and control of the systems. Normally these systems ...
Energy management in a hybrid PV/wind/battery system using a type-1 fuzzy logic computer algorithm
This paper presents a computer algorithm based on fuzzy logic control to manage the flow of energy in a stand-alone PV/wind/battery hybrid system. The system is composed of 16 photovoltaic PV solar panels, one wind turbine and two batteries. The solar ...
Comments