The operational efficiency of remote environmental wireless sensor networks (EWSNs) has improved tremendously with the advent of Internet of Things (IoT) technologies over the past few years. EWSNs require elaborate device composition and advanced control to attain long-term operation with minimal maintenance. This article is focused on power supplies that provide energy to run the wireless sensor nodes in environmental applications. In this context, EWSNs have two distinct features that set them apart from monitoring systems in other application domains. They are often deployed in remote areas, preventing the use of mains power and precluding regular visits to exchange batteries. At the same time, their surroundings usually provide opportunities to harvest ambient energy and use it to (partially) power the sensor nodes. This review provides a comprehensive account of energy harvesting sources, energy storage devices, and corresponding topologies of energy harvesting systems, focusing on studies published within the last 10 years. Current trends and future directions in these areas are also covered.

Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6G 1H9 Canada

Faculty of Computer Science VSB Technical University of Ostrava 708 33 Ostrava Czech Republic

Zobrazit více v PubMed

Musilek P., Prauzek M., Kromer P., Rodway J., Barton T. Intelligent Energy Management for Environmental Monitoring Systems. Smart Sens. Netw. 2017:67–94. doi: 10.1016/B978-0-12-809859-2.00005-X. DOI

Prauzek M., Kromer P., Rodway J., Musilek P. Differential evolution of fuzzy controller for environmentally-powered wireless sensors. Appl. Soft Comput. J. 2016;48:193–206. doi: 10.1016/j.asoc.2016.06.040. DOI

Sundaran K., Murugaanandam S., Ganapathy V. Energy efficient techniques in wireless sensor networks: Recent survey. Sens. Lett. 2016;14:643–655. doi: 10.1166/sl.2016.3588. DOI

Prauzek M., Musilek P., Watts A. Fuzzy algorithm for intelligent wireless sensors with solar harvesting; Proceedings of the 2014 IEEE Symposium Series on Computational Intelligence; Orlando, FL, USA. 9–12 December 2014; pp. 1–7.

Shaikh F.K., Zeadally S. Energy harvesting in wireless sensor networks: A comprehensive review. Renew. Sustain. Energy Rev. 2016;55:1041–1054. doi: 10.1016/j.rser.2015.11.010. DOI

Jiao P., Borchani W., Hasni H., Lajnef N. Enhancement of quasi-static strain energy harvesters using non-uniform cross-section post-buckled beams. Smart Mater. Struct. 2017;26:085045. doi: 10.1088/1361-665X/aa746e. DOI

Shad R., Steingart D., Frechette L., Wright P., Rabaey J. Power Sources for Wireless Sensor Networks. In: Karl H., Wolisz A., Willig A., editors. Wireless Sensor Networks. Springer; Berlin/Heidelberg, Germany: 2004. pp. 1–17.

Mousavi S.M., Mostafavi E.S., Jiao P. Next generation prediction model for daily solar radiation on horizontal surface using a hybrid neural network and simulated annealing method. Energy Convers. Manag. 2017;153:671–682. doi: 10.1016/j.enconman.2017.09.040. DOI

Milichko V.A., Shalin A.S., Mukhin I.S., Kovrov A.E., Krasilin A.A., Vinogradov A.V., Belov P.A., Simovski C.R. Solar photovoltaics: Current state and trends. Physics-Uspekhi. 2016;59:727. doi: 10.3367/UFNe.2016.02.037703. DOI

Mungan E.S., Lu C., Raghunathan V., Roy K. Modeling, Design and Cross-layer Optimization of Polysilicon Solar Cell Based Micro-scale Energy Harvesting Systems; Proceedings of the 2012 ACM/IEEE International Symposium on Low Power Electronics and Design; Redondo Beach, CA, USA. 30 July–1 August 2012; pp. 123–128.

Akhtar F., Rehmani M.H. Energy replenishment using renewable and traditional energy resources for sustainable wireless sensor networks: A review. Renew. Sustain. Energy Rev. 2015;45:769–784. doi: 10.1016/j.rser.2015.02.021. DOI

Panatik K., Kamardin K., Shariff S., Yuhaniz S., Ahmad N., Yusop O., Ismail S. Energy harvesting in wireless sensor networks: A survey; Proceedings of the 2016 IEEE 3rd International Symposium on Telecommunication Technologies; Kuala Lumpur, Malaysia. 28–30 November 2016; pp. 53–58.

Raghunathan V., Kansal A., Hsu J., Friedman J., Srivastava M. Design considerations for solar energy harvesting wireless embedded systems; Proceedings of the 2005 4th International Symposium on Information Processing in Sensor Networks; Boise, ID, USA. 15 April 2005; pp. 457–462.

Sudevalayam S., Kulkarni P. Energy Harvesting Sensor Nodes: Survey and Implications. IEEE Commun. Surv. Tutor. 2011;13:443–461. doi: 10.1109/SURV.2011.060710.00094. DOI

Kelly N.A., Gibson T.L. Increasing the solar photovoltaic energy capture on sunny and cloudy days. Sol. Energy. 2011;85:111–125. doi: 10.1016/j.solener.2010.10.015. DOI

Shao H., Tsui C.Y., Ki W.H. A micro power management system and maximum output power control for solar energy harvesting applications; Proceedings of the 2007 ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED); Portland, OR, USA. 27–29 August 2007; pp. 298–303.

Shao H., Tsui C.Y., Ki W.H. An inductor-less micro solar power management system design for energy harvesting applications; Proceedings of the 2007 IEEE International Symposium on Circuits and Systems; New Orleans, LA, USA. 27–30 May 2007; pp. 1353–1356.

Bardwell M., Wong J., Zhang S., Musilek P. Design Considerations for IoT-based PV Charge Controllers; Proceedings of the IEEE World Congress on Services; San Francisco, CA, USA. 2–7 July 2018.

Zhou G., Huang L., Li W., Zhu Z. Harvesting ambient environmental energy for wireless sensor networks: A survey. J. Sens. 2014;2014:815467. doi: 10.1155/2014/815467. DOI

Zou T., Lin S., Feng Q., Chen Y. Energy-efficient control with harvesting predictions for solar-powered wireless sensor networks. Sensors. 2016;16:53. doi: 10.3390/s16010053. PubMed DOI PMC

Buchli B., Sutton F., Beutel J., Thiele L. Towards Enabling Uninterrupted Long-Term Operation of Solar Energy Harvesting Embedded Systems; Proceedings of the 11th European Conference on Wireless Sensor Networks; Oxford, UK. 17–19 February 2014; Berlin, Germany: Springer; 2014. pp. 66–83. Lecture Notes in Computer Science.

Li Y., Shi R. An intelligent solar energy-harvesting system for wireless sensor networks. EURASIP J. Wirel. Commun. Netw. 2015;2015:179. doi: 10.1186/s13638-015-0414-2. DOI

Kim S., Chou P.H. Energy harvesting by sweeping voltage-escalated charging of a reconfigurable supercapacitor array; Proceedings of the 17th IEEE/ACM International Symposium on Low-Power Electronics and Design; Fukuoka, Japan. 1–3 August 2011; pp. 235–240.

Nguyen N.Q., Pochiraju K.V. Behavior of thermoelectric generators exposed to transient heat sources. Appl. Therm. Eng. 2013;51:1–9. doi: 10.1016/j.applthermaleng.2012.08.050. DOI

Penella-López M.T., Gasulla-Forner M. Powering Autonomous Sensors. Springer; Berlin, Germany: 2011.

Datta U., Dessouky S., Papagiannakis A. Harvesting thermoelectric energy from asphalt pavements. Transp. Res. Rec. 2017;2628:12–22. doi: 10.3141/2628-02. DOI

Mendonça F., Azevedo J. Design and power production of small-scale wind turbines; Proceedings of the 2017 International Conference in Energy and Sustainability in Small Developing Economies (ES2DE); Funchal, Portugal. 10–12 July 2017.

Pimentel D., Musilek P., Knight A., Heckenbergerova J. Characterization of a wind flutter generator; Proceedings of the 2010 9th Conference on Environment and Electrical Engineering; Prague, Czech Republic. 16–19 May 2010; pp. 81–84.

Carli D., Brunelli D., Bertozzi D., Benini L. A high-efficiency wind-flow energy harvester using micro turbine; Proceedings of the 2010 International Symposium on Power Electronics Electrical Drives Automation and Motion (SPEEDAM); Pisa, Italy. 14–16 June 2010; pp. 778–783.

Tan Y.K., Panda S.K. Optimized wind energy harvesting system using resistance emulator and active rectifier for wireless sensor nodes. IEEE Trans. Power Electron. 2011;26:38–50.

Jushi A., Pegatoquet A., Le T.N. Wind Energy Harvesting for Autonomous Wireless Sensor Networks; Proceedings of the 2016 Euromicro Conference on Digital System Design (DSD); Limassol, Cyprus. 31 August–2 September 2016; pp. 301–308.

Baranov A., Spirjakin D., Akbari S., Somov A., Passerone R. POCO: ‘Perpetual’ operation of CO wireless sensor node with hybrid power supply. Sens. Actuators A Phys. 2016;238:112–121. doi: 10.1016/j.sna.2015.12.004. DOI

Kim S., Vyas R., Bito J., Niotaki K., Collado A., Georgiadis A., Tentzeris M. Ambient RF energy-harvesting technologies for self-sustainable standalone wireless sensor platforms. Proc. IEEE. 2014;102:1649–1666. doi: 10.1109/JPROC.2014.2357031. DOI

Kamalinejad P., Mahapatra C., Sheng Z., Mirabbasi S., Leung V., Guan Y. Wireless Energy Harvesting for the Internet of Things. IEEE Commun. Mag. 2015;53:102–108. doi: 10.1109/MCOM.2015.7120024. DOI

Dinesh Kumar K., Hemalatha M. Designing EM energy harvesting antenna to give power support to embedded sensor. Int. J. Appl. Eng. Res. 2014;9:1565–1574.

Lorenz C., Hemour S., Li W., Xie Y., Gauthier J., Fay P., Wu K. Breaking the Efficiency Barrier for Ambient Microwave Power Harvesting with Heterojunction Backward Tunnel Diodes. IEEE Trans. Microw. Theory Tech. 2015;63:4544–4555. doi: 10.1109/TMTT.2015.2495356. DOI

Vyas R., Cook B., Kawahara Y., Tentzeris M. E-WEHP: A batteryless embedded sensor-platform wirelessly powered from ambient digital-TV signals. IEEE Trans. Microw. Theory Tech. 2013;61:2491–2505. doi: 10.1109/TMTT.2013.2258168. DOI

Habibzadeh M., Hassanalieragh M., Ishikawa A., Soyata T., Sharma G. Hybrid Solar-Wind Energy Harvesting for Embedded Applications: Supercapacitor-Based System Architectures and Design Tradeoffs. IEEE Circuits Syst. Mag. 2017;17:29–63. doi: 10.1109/MCAS.2017.2757081. DOI

Ertugrul N. Battery storage technologies, applications and trend in renewable energy; Proceedings of the 2016 IEEE International Conference on Sustainable Energy Technologies (ICSET); Hanoi, Vietnam. 14–16 November 2016; pp. 420–425.

Tan X., Li Q., Wang H. Advances and trends of energy storage technology in Microgrid. Int. J. Electr. Power Energy Syst. 2013;44:179–191. doi: 10.1016/j.ijepes.2012.07.015. DOI

Sullivan J., Gaines L. A Review of Battery Life-Cycle Analysis: State of Knowledge and Critical Needs. Argonne National Laboratory (ANL); Du Page County, IL, USA: 2010. Technical Report.

Aneke M., Wang M. Energy storage technologies and real life applications–A state of the art review. Appl. Energy. 2016;179:350–377. doi: 10.1016/j.apenergy.2016.06.097. DOI

Zhang C., Wei Y.L., Cao P.F., Lin M.C. Energy storage system: Current studies on batteries and power condition system. Renew. Sustain. Energy Rev. 2017;82:3091–3106. doi: 10.1016/j.rser.2017.10.030. DOI

Taneja J., Jeong J., Culler D. Design, modeling, and capacity planning for micro-solar power sensor networks; Proceedings of the 7th International Conference on Information Processing in Sensor Networks; St. Louis, MO, USA. 22–24 April 2008; Washington, DC, USA: IEEE Computer Society; 2008. pp. 407–418.

Yadav G.G., Wei X., Huang J., Turney D., Nyce M., Banerjee S. Accessing the second electron capacity of MnO2 by exploring complexation and intercalation reactions in energy dense alkaline batteries. Int. J. Hydrog. Energy. 2018;43:8480–8487. doi: 10.1016/j.ijhydene.2018.03.061. DOI

Akinyele D., Rayudu R. Review of energy storage technologies for sustainable power networks. Sustain. Energy Technol. Assess. 2014;8:74–91. doi: 10.1016/j.seta.2014.07.004. DOI

Kaldellis J., Zafirakis D. Optimum energy storage techniques for the improvement of renewable energy sources-based electricity generation economic efficiency. Energy. 2007;32:2295–2305. doi: 10.1016/j.energy.2007.07.009. DOI

Zou C., Zhang L., Hu X., Wang Z., Wik T., Pecht M. A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors. J. Power Sources. 2018;390:286–296. doi: 10.1016/j.jpowsour.2018.04.033. DOI

Bradbury K. Energy Storage Technology Review. Duke University; Durham, NC, USA: 2010. pp. 1–34.

Okonkwo P., Collins E., Okonkwo E. Biopolymer Composites in Electronics. Elsevier; New York, NY, USA: 2017. Application of Biopolymer Composites in Super Capacitor; pp. 487–503.

Libich J., Máca J., Vondrák J., Čech O., Sedlaříková M. Supercapacitors: Properties and applications. J. Energy Storage. 2018;17:224–227. doi: 10.1016/j.est.2018.03.012. DOI

Merrett G., Weddell A. Supercapacitor leakage in energy-harvesting sensor nodes: Fact or fiction?; Proceedings of the 9th International Conference on Networked Sensing Systems; Antwerp, Belgium. 11–14 June 2012.

Renner C., Jessen J., Turau V. Lifetime prediction for supercapacitor-powered wireless sensor nodes; Proceedings of the GI/ITG Fachgespräch “Sensornetze” (FGSN’09); Humburg, Germany. 13 August 2009; pp. 1–6.

Luo X., Wang J., Dooner M., Clarke J. Overview of current development in electrical energy storage technologies and the application potential in power system operation. Appl. Energy. 2015;137:511–536. doi: 10.1016/j.apenergy.2014.09.081. DOI

Simjee F.I., Chou P.H. Efficient charging of supercapacitors for extended lifetime of wireless sensor nodes. IEEE Trans. Power Electr. 2008;23:1526–1536. doi: 10.1109/TPEL.2008.921078. DOI

Piller S., Perrin M., Jossen A. Methods for state-of-charge determination and their applications. J. Power Sources. 2001;96:113–120. doi: 10.1016/S0378-7753(01)00560-2. DOI

Ng K., Moo C.S., Chen Y.P., Hsieh Y.C. Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries. Appl. Energy. 2009;86:1506–1511. doi: 10.1016/j.apenergy.2008.11.021. DOI

Kalawoun J., Biletska K., Suard F., Montaru M. From a novel classification of the battery state of charge estimators toward a conception of an ideal one. J. Power Sources. 2015;279:694–706. doi: 10.1016/j.jpowsour.2015.01.038. DOI

Pop V., Bergveld H., Notten P., Regtien P. State-of-the-art of battery state-of-charge determination. Meas. Sci. Technol. 2005;16:R93–R110. doi: 10.1088/0957-0233/16/12/R01. DOI

Coleman M., Lee C., Zhu C., Hurley W. State-of-charge determination from EMF voltage estimation: Using impedance, terminal voltage, and current for lead-acid and lithium-ion batteries. IEEE Trans. Ind. Electr. 2007;54:2550–2557. doi: 10.1109/TIE.2007.899926. DOI

Lv W., Li Z., Deng Y., Yang Q.H., Kang F. Graphene-based materials for electrochemical energy storage devices: Opportunities and challenges. Energy Storage Mater. 2016;2:107–138. doi: 10.1016/j.ensm.2015.10.002. DOI

Song J., Xu T., Gordin M.L., Zhu P., Lv D., Jiang Y.B., Chen Y., Duan Y., Wang D. Nitrogen-Doped Mesoporous Carbon Promoted Chemical Adsorption of Sulfur and Fabrication of High-Areal-Capacity Sulfur Cathode with Exceptional Cycling Stability for Lithium-Sulfur Batteries. Adv. Funct. Mater. 2014;24:1243–1250. doi: 10.1002/adfm.201302631. DOI

Li W., Yang Z., Li M., Jiang Y., Wei X., Zhong X., Gu L., Yu Y. Amorphous red phosphorus embedded in highly ordered mesoporous carbon with superior lithium and sodium storage capacity. Nano Lett. 2016;16:1546–1553. doi: 10.1021/acs.nanolett.5b03903. PubMed DOI

Bichat M., Raymundo-Piñero E., Béguin F. High voltage supercapacitor built with seaweed carbons in neutral aqueous electrolyte. Carbon. 2010;48:4351–4361. doi: 10.1016/j.carbon.2010.07.049. DOI

Newell R., Faure-Vincent J., Iliev B., Schubert T., Aradilla D. A new high performance ionic liquid mixture electrolyte for large temperature range supercapacitor applications (−70 °C to 80 °C) operating at 3.5 V cell voltage. Electrochim. Acta. 2018;267:15–19. doi: 10.1016/j.electacta.2018.02.067. DOI

Khomenko V., Raymundo-Pinero E., Frackowiak E., Beguin F. High-voltage asymmetric supercapacitors operating in aqueous electrolyte. Appl. Phys. A. 2006;82:567–573. doi: 10.1007/s00339-005-3397-8. DOI

Kansal A., Potter D., Srivastava M. Performance aware tasking for environmentally powered sensor networks. Perform. Eval. Rev. 2004;32:223–234. doi: 10.1145/1012888.1005714. DOI

Vigorito C., Ganesan D., Barto A. Adaptive control of duty cycling in energy-harvesting wireless sensor networks; Proceedings of the 2007 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks; San Diego, CA, USA. 18–21 June 2007; pp. 21–30.

Hsu J., Zahedi S., Kansal A., Srivastava M., Raghunathan V. Adaptive duty cycling for energy harvesting systems; Proceedings of the International Symposium on Low Power Electronics and Design; Tegernsee, Germany. 4–6 October 2006; pp. 180–185.

Kansal A., Hsu J., Srivastava M., Raghunathan V. Harvesting aware power management for sensor networks; Proceedings of the 43rd Annual Design Automation Conference; San Francisco, CA, USA. 24–28 July 2006; pp. 651–656.

Raghunathan V., Chou P.H. Design and Power Management of Energy Harvesting Embedded Systems; Proceedings of the 2006 International Symposium on Low Power Electronics and Design; Tegernsee, Germany. 4–6 October 2006; pp. 369–374.

Kansal A., Hsu J., Zahedi S., Srivastava M.B. Power management in energy harvesting sensor networks. ACM Trans. Embed. Comput. Syst. 2007;6 doi: 10.1145/1274858.1274870. DOI

Pimentel D., Musilek P. Power management with energy harvesting devices; Proceedings of the 2010 23rd Canadian Conference on Electrical and Computer Engineering (CCECE); Calgary, AB, Canada. 2–5 May 2010; pp. 1–4.

Pirapaharan K., Gunathillake W., Lokunarangoda G., Nissansani M., Palihena H., Hoole P., Aravind C., Hoole S. Design of a battery-less micro-scale RF energy harvester for medical devices; Proceedings of the 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences; Langkawi, Malaysia. 17–19 December 2012; pp. 270–272.

Yi J., Su F., Lam Y.H., Ki W.H., Tsui C.Y. An energy-adaptive MPPT power management unit for micro-power vibration energy harvesting; Proceedings of the IEEE International Symposium on Circuits and Systems; Seattle, WA, USA. 18–21 May 2008; pp. 2570–2573.

Bergonzini C., Brunelli D., Benini L. Algorithms for harvested energy prediction in batteryless wireless sensor networks; Proceedings of the 3rd International Workshop on Advances in Sensors and Interfaces; Trani, Italy. 25–26 June 2009; pp. 144–149.

Liu S., Lu J., Wu Q., Qiu Q. Harvesting-aware power management for real-time systems with renewable energy. IEEE Trans. Very Large Scale Integr. (VLSI) Syst. 2012;20:1473–1486.

Lu C., Park S.P., Raghunathan V., Roy K. Stage number optimization for switched capacitor power converters in micro-scale energy harvesting; Proceedings of the 2011 Design, Automation & Test in Europe; Grenoble, France. 14–18 March 2011; pp. 1–6.

Lu C., Raghunathan V., Roy K. Efficient design of micro-scale energy harvesting systems. IEEE J. Emerg. Sel. Top. Circuits Syst. 2011;3:254–266. doi: 10.1109/JETCAS.2011.2162161. DOI

Janek A., Steger C., Preishuber-Pfluegl J., Pistauer M. Power management strategies for battery-driven higher Class UHF RFID tags supported by energy harvesting devices; Proceedings of the 2007 IEEE Workshop on Automatic Identification Advanced Technologies; Alghero, Italy. 7–8 June 2007; pp. 122–127.

Watts A., Prauzek M., Musilek P., Pelikan E., Sanchez-Azofeifa A. Fuzzy power management for environmental monitoring systems in tropical regions; Proceedings of the International Joint Conference on Neural Networks; Beijing, China. 6–11 July 2014; pp. 1719–1726.

Prauzek M., Musilek P., Watts A., Michalikova M. Powering environmental monitoring systems in arctic regions: A simulation study. Elektron. Elektrotech. 2014;20:34–37. doi: 10.5755/j01.eee.20.7.8020. DOI

Krömer P., Prauzek M., Musilek P., Barton T. Optimization of Wireless Sensor Node Parameters by Differential Evolution and Particle Swarm Optimization. Adv. Intell. Syst. Comput. 2014;303:13–22.

Prauzek M., Mourcet M., Hlavica J., Musilek P. Q-learning Algorithm for Energy Management in Solar Powered Embedded Monitoring Systems; Proceedings of the 2018 IEEE Congress on Evolutionary Computation; Rio de Janeiro, Brazil. 8 July 2018.

Pötsch A., Haslhofer F. Practical limitations for deployment of LoRa gateways; Proceedings of the 2017 IEEE International Workshop on Measurement and Networking; Naples, Italy. 27–29 September 2017.

Lee D., Dulai G., Karanassios V. Survey of energy harvesting and energy scavenging approaches for on-site powering of wireless sensor- and microinstrument-networks. Proc. SPIE. 2013;8728 doi: 10.1117/12.2016238. DOI

Bhuyan S., Hu J. A natural battery based on lake water and its soil bank. Energy. 2013;51:395–399. doi: 10.1016/j.energy.2012.12.044. DOI

Trizcinski P., Nathan A., Karanassios V. Approaches to energy harvesting and energy scavenging for energy autonomous sensors and microinstruments. Proc. SPIE. 2017;10194 doi: 10.1117/12.2262957. DOI

McGarry S., Knight C. The potential for harvesting energy from the movement of trees. Sensors. 2011;11:9275–9299. doi: 10.3390/s111009275. PubMed DOI PMC

McGarry S., Knight C. Development and successful application of a tree movement energy harvesting device, to power a wireless sensor node. Sensors. 2012;12:12110–12125. doi: 10.3390/s120912110. DOI

Asadi M., Sayahpour B., Abbasi P., Ngo A.T., Karis K., Jokisaari J.R., Liu C., Narayanan B., Gerard M., Yasaei P., et al. A lithium-oxygen battery with a long cycle life in an air-like atmosphere. Nature. 2018;555:502–506. doi: 10.1038/nature25984. PubMed DOI

Wu F., Yu Y. Toward True Lithium-Air Batteries. Joule. 2018;2:815–817. doi: 10.1016/j.joule.2018.04.019. DOI

Ulukus S., Yener A., Erkip E., Simeone O., Zorzi M., Grover P., Huang K. Energy harvesting wireless communications: A review of recent advances. IEEE J. Sel. Areas Commun. 2015;33:360–381. doi: 10.1109/JSAC.2015.2391531. DOI

Gallegos A., Noguchi T., Izumi T., Nakatani Y. Zone-based energy aware data collection protocol for WSNs. IEICE Trans. Commun. 2018;E101B:750–762. doi: 10.1587/transcom.2017EBP3133. DOI

Zeng D., Li P., Guo S., Miyazaki T., Hu J., Xiang Y. Energy Minimization in Multi-Task Software-Defined Sensor Networks. IEEE Trans. Comput. 2015;64:3128–3139. doi: 10.1109/TC.2015.2389802. DOI

Ahmad M., Mourshed M., Mundow D., Sisinni M., Rezgui Y. Building energy metering and environmental monitoring—A state-of-the-art review and directions for future research. Energy Build. 2016;120:85–102. doi: 10.1016/j.enbuild.2016.03.059. DOI

Raza U., Kulkarni P., Sooriyabandara M. Low Power Wide Area Networks: An Overview. IEEE Commun. Surv. Tutor. 2017;19:855–873. doi: 10.1109/COMST.2017.2652320. DOI

Yue Y., He P. A comprehensive survey on the reliability of mobile wireless sensor networks: Taxonomy, challenges, and future directions. Inf. Fusion. 2018;44:188–204. doi: 10.1016/j.inffus.2018.03.005. DOI

Yick J., Mukherjee B., Ghosal D. Wireless sensor network survey. Comput. Netw. 2008;52:2292–2330. doi: 10.1016/j.comnet.2008.04.002. DOI

Powering Agriculture IoT Sensors Using Natural Temperature Differences Between Air and Soil: Measurement and Evaluation

Environment-Monitoring IoT Devices Powered by a TEG Which Converts Thermal Flux between Air and Near-Surface Soil into Electrical Energy