Abstract

The incorporation of renewable energy sources and the efficient utilization of energy are crucial factors in facilitating sustainable energy transitions and addressing the issue of climate change. The Internet of Things (IoT) is a modern technology that has numerous applications in the energy sector. These applications include energy supply, transmission and distribution, as well as demand management. The utilization of IoT can enhance energy efficiency, augment the proportion of renewable energy, and mitigate the environmental consequences of energy consumption. This study examines the current body of literature about the use of Internet of Things (IoT) technology in energy systems, with a specific focus on its application in smart grids. In addition, we explore the enabling technologies of the Internet of Things (IoT), such as cloud computing and other platforms for data analysis.

References

• Stearns, P.N. Reconceptualizing the Industrial Revolution. J. Interdiscip. Hist. 2011, 42, 442–443.
• Mokyr, J. The second industrial revolution, 1870–1914. In Storia dell’Economia Mondiale; Citeseer, 1998; pp. 219–245. Available online: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.481.2996&rep=rep1&type=pdf (accessed on 30 August 2024).
• Jensen, M. The Modern Industrial Revolution, Exit, and the Failure of Internal Control Systems. J. Financ. 1993, 48, 831–880.
• Kagermann, H.; Helbig, J.; Hellinger, A.; Wahlster, W. Recommendations for Implementing the Strategic Initiative Industrie 4.0: Securing the Future of German Manufacturing Industry; Final Report of the Industrie 4.0 Working Group; Forschungsunion: Frankfurt/Main, Germany, 2013.
• Witchalls, C.; Chambers, J. The Internet of Things Business Index: A Quiet Revolution Gathers Pace; The Economist Intelligence Unit: London, UK, 2013; pp. 58–66.
• Datta, S.K.; Bonnet, C. MEC and IoT Based Automatic Agent Reconfiguration in Industry 4.0. In Proceedings of the 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), Indore, India, 16–19 December 2018; pp. 1–5.
• Shrouf, F.; Ordieres, J.; Miragliotta, G. Smart factories in Industry 4.0: A review of the concept and of energy management approached in production based on the Internet of Things paradigm. In Proceedings of the 2014 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Selangor Darul Ehsan, Malaysia, 9–12 December 2014; pp. 697–701.
• Bandyopadhyay, D.; Sen, J. Internet of Things: Applications and Challenges in Technology and Standardization. Wirel. Pers. Commun. 2011, 58, 49–69.
• International Energy Agency (IEA). Global Energy & CO2 Status Report. 2019. Available online: https://www.iea.org/geco/
• Intergovernmental Panel for Climate Change (IPCC). Global Warning of 1.5 °C: Summary for Policymakers. 2018. Available online: https://www.ipcc.ch/sr15/chapter/spm/
• Zakeri, B.; Syri, S.; Rinne, S. Higher renewable energy integration into the existing energy system of Finland–Is there any maximum limit? Energy 2015, 92, 244–259.
• Connolly, D.; Lund, H.; Mathiesen, B. Smart Energy Europe: The technical and economic impact of one potential 100% renewable energy scenario for the European Union. Renew. Sustain. Energy Rev. 2016, 60, 1634–1653.
• Grubler, A.; Wilson, C.; Bento, N.; Boza-Kiss, B.; Krey, V.; McCollum, D.L.; Rao, N.D.; Riahi, K.; Rogelj, J.; De Stercke, S.; et al. A low energy demand scenario for meeting the 1.5 C target and sustainable development goals without negative emission technologies. Nat. Energy 2018, 3, 515–527.
• UN. Special Edition: Progress towards the Sustainable Development Goals; UN: New York, NY, USA, 2019.
• Tan, Y.S.; Ng, Y.T.; Low, J.S.C. Internet-of-things enabled real-time monitoring of energy efficiency on manufacturing shop floors. Procedia CIRP 2017, 61, 376–381.
• Bhattacharyya, S.C. Energy Economics: Concepts, Issues, Markets and Governance; Springer: Berlin/Heidelberg, Germany, 2011.
• Tamilselvan, K.; Thangaraj, P. Pods—A novel intelligent energy efficient and dynamic frequency scalings for multi-core embedded architectures in an IoT environment. Microprocess. Microsyst. 2020, 72, 102907.
• Zhou, K.; Yang, S.; Shao, Z. Energy Internet: The business perspective. Appl. Energy 2016, 178, 212–222.
• Motlagh, N.H.; Khajavi, S.H.; Jaribion, A.; Holmstrom, J. An IoT-based automation system for older homes: A use case for lighting system. In Proceedings of the 2018 IEEE 11th Conference on Service-Oriented Computing and Applications (SOCA), Paris, France, 19–22 November 2018; pp. 1–6.
• Da Xu, L.; He, W.; Li, S. Internet of Things in Industries: A Survey. IEEE Trans. Ind. Inform. 2014, 10, 2233–2243.
• Talari, S.; Shafie-Khah, M.; Siano, P.; Loia, V.; Tommasetti, A.; Catalão, J. A review of smart cities based on the internet of things concept. Energies 2017, 10, 421.
• Ibarra-Esquer, J.; González-Navarro, F.; Flores-Rios, B.; Burtseva, L.; Astorga-Vargas, M. Tracking the evolution of the internet of things concept across different application domains. Sensors 2017, 17, 1379.
• Swan, M. Sensor mania! the internet of things, wearable computing, objective metrics, and the quantified self 2.0. J. Sens. Actuator Netw. 2012, 1, 217–253.
• Gupta, A.; Jha, R.K. A survey of 5G network: Architecture and emerging technologies. IEEE Access 2015, 3, 1206–1232.
• Stojkoska, B.L.R.; Trivodaliev, K.V. A review of Internet of Things for smart home: Challenges and solutions. J. Clean. Prod. 2017, 140, 1454–1464.
• Hui, H.; Ding, Y.; Shi, Q.; Li, F.; Song, Y.; Yan, J. 5G network-based Internet of Things for demand response in smart grid: A survey on application potential. Appl. Energy 2020, 257, 113972.
• Petroșanu, D.M.; Căruțașu, G.; Căruțașu, N.L.; Pîrjan, A. A Review of the Recent Developments in Integrating Machine Learning Models with Sensor Devices in the Smart Buildings Sector with a View to Attaining Enhanced Sensing, Energy Efficiency, and Optimal Building Management. Energies 2019, 12, 4745.
• Luo, X.G.; Zhang, H.B.; Zhang, Z.L.; Yu, Y.; Li, K. A New Framework of Intelligent Public Transportation System Based on the Internet of Things. IEEE Access 2019, 7, 55290–55304.
• Khatua, P.K.; Ramachandaramurthy, V.K.; Kasinathan, P.; Yong, J.Y.; Pasupuleti, J.; Rajagopalan, A. Application and Assessment of Internet of Things toward the Sustainability of Energy Systems: Challenges and Issues. Sustain. Cities Soc. 2019, 101957.
• Haseeb, K.; Almogren, A.; Islam, N.; Ud Din, I.; Jan, Z. An Energy-Efficient and Secure Routing Protocol for Intrusion Avoidance in IoT-Based WSN. Energies 2019, 12, 4174.
• Zouinkhi, A.; Ayadi, H.; Val, T.; Boussaid, B.; Abdelkrim, M.N. Auto-management of energy in IoT networks. Int. J. Commun. Syst. 2019, 33, e4168.
• Höller, J.; Tsiatsis, V.; Mulligan, C.; Avesand, S.; Karnouskos, S.; Boyle, D. From Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence; Elsevier: Amsterdam, The Netherlands, 2014.
• Atzori, L.; Iera, A.; Morabito, G. The Internet of Things: A survey. Comput. Netw. 2010, 54, 2787–2805.
• Hui, T.K.; Sherratt, R.S.; Sánchez, D.D. Major requirements for building Smart Homes in Smart Cities based on Internet of Things technologies. Future Gener. Comput. Syst. 2017, 76, 358–369.
• Evans, D. The Internet of Things: How the Next Evolution of the Internet is Changing Everything. CISCO White Pap. 2011, 1, 1–11.
• Motlagh, N.H.; Bagaa, M.; Taleb, T. Energy and Delay Aware Task Assignment Mechanism for UAV-Based IoT Platform. IEEE Internet Things J. 2019, 6, 6523–6536.
• Ramamurthy, A.; Jain, P. The Internet of Things in the Power Sector: Opportunities in Asia and the Pacific; Asian Development Bank: Mandaluyong, Philippines, 2017.
• Jia, M.; Komeily, A.; Wang, Y.; Srinivasan, R.S. Adopting Internet of Things for the development of smart buildings: A review of enabling technologies and applications. Autom. Constr. 2019, 101, 111–126.
• Karunarathne, G.R.; Kulawansa, K.T.; Firdhous, M.M. Wireless Communication Technologies in Internet of Things: A Critical Evaluation. In Proceedings of the 2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC), Plaine Magnien, Mauritius, 6–7 December 2018; pp. 1–5.
• Li, S.; Da Xu, L.; Zhao, S. 5G Internet of Things: A survey. J. Ind. Inf. Integr. 2018, 10, 1–9.
• Watson Internet of Things. Securely Connect with Watson IoT Platform. 2019. Available online: https://www.ibm.com/internet-of-things/solutions/iot-platform/watson-iot-platform (accessed on 30 August 2024).
• Ehsan Bazgir, Ehteshamul Haque, Md. Maniruzzaman and Rahmanul Hoque, “Skin cancer classification using Inception Network”, World Journal of Advanced Research and Reviews, 2024, 21(02), 839–849.
• Rahmanul Hoque, Suman Das, Mahmudul Hoque and Ehteshamul Haque, “Breast Cancer Classification using XGBoost”, World Journal of Advanced Research and Reviews, 2024, 21(02), 1985–1994
• Rahmanul Hoque, Masum Billah, Amit Debnath, S. M. Saokat Hossain and Numair Bin Sharif, “Heart Disease Prediction using SVM”, International Journal of Science and Research Archive, 2024, 11(02), 412–420.
• Rahmanul Hoque, Md. Maniruzzaman, Daniel Lucky Michael and Mahmudul Hoque, “Empowering blockchain with SmartNIC: Enhancing performance, security, and scalability”, World Journal of Advanced Research and Reviews, 2024, 22(01), 151–162
• Tonyali S., Cakmak O., Akkaya K., Mahmoud M.M.E.A., Guvenc I. Secure data obfuscation scheme to enable privacy-preserving state estimation in smart grid AMI networks IEEE Internet Things J., 3 (5) (2016), pp. 709-719, 10.1109/JIOT.2015.2510504
• Buswig Y.M., Affam A., Albalawi H., Julai N., Hj A., Qays O. Development and modelling of three phase inverter for harmonic improvement using sinusoidal pulse width modulation (SPWM) control technique Int. J. Recent Technol. Eng., 8 (4) (2019), pp. 1897-1902.
• Qays, M. O., Ahmad, I., Abu-Siada, A., Hossain, M. L., & Yasmin, F. (2023). Key communication technologies, applications, protocols and future guides for IoT-assisted smart grid systems: A review. Energy Reports, 9, 2440-2452.
• Atasoy T., Akinc H.E., Ercin O. An analysis on smart grid applications and grid integration of renewable energy systems in smart cities 2015 Int. Conf. Renew. Energy Res. Appl. ICRERA 2015 (2015), pp. 547-550.
• Hu Q., Li F. Hardware design of smart home energy management system with dynamic price response IEEE Trans. Smart Grid, 4 (4) (2013), pp. 1878-1887, 10.1109/TSG.2013.2258181
• Viani F., Robol F., Polo A., Rocca P., Oliveri G., Massa A. Wireless architectures for heterogeneous sensing in smart home applications: Concepts and real implementation Proc. IEEE, 101 (11) (2013), pp. 2381-2396, 10.1109/JPROC.2013.2266858
• Wu, S.W., 2011. Research on the key technologies of IOT applied on Smart Grid. In: 2011 Int. Conf. Electron. Commun. Control. ICECC 2011 - Proc. pp. 2809–2812.
• Wang Y.F., Lin W.M., Zhang T., Ma Y.Y. Research on application and security protection of internet of things in smart grid IET Conf. Publ. vol. 2012 no. 636, CP (2012), 10.1049/CP.2012.2311
• Kshetri, N. Can Blockchain Strengthen the Internet of Things? IT Prof. 2017, 19, 68–72.
• Dorri, A.; Kanhere, S.S.; Jurdak, R. Towards an optimized blockchain for IoT. In Proceedings of the Second International Conference on Internet-of-Things Design and Implementation, Pittsburgh, PA, USA, 18–21 April 2017; pp. 173–178.
• Huh, S.; Cho, S.; Kim, S. Managing IoT devices using blockchain platform. In Proceedings of the 2017 19th International Conference on Advanced Communication Technology (ICACT), Bongpyeong, Korea, 19–22 February 2017; pp. 464–467.
• Alladi, T.; Chamola, V.; Rodrigues, J.J.; Kozlov, S.A. Blockchain in Smart Grids: A Review on Different Use Cases. Sensors 2019, 19, 4862.
• Christidis, K.; Devetsikiotis, M. Blockchains and Smart Contracts for the Internet of Things. IEEE Access 2016, 4, 2292–2303.
• Korpela, K.; Hallikas, J.; Dahlberg, T. Digital Supply Chain Transformation toward Blockchain Integration. In Proceedings of the 50th Hawaii International Conference on Ssystem Sciences, Waikoloa, HI, USA, 4–7 January 2017.
• Hawlitschek, F.; Notheisen, B.; Teubner, T. The limits of trust-free systems: A literature review on blockchain technology and trust in the sharing economy. Electron. Commer. Res. Appl. 2018, 29, 50–63.
• Conoscenti, M.; Vetro, A.; De Martin, J.C. Blockchain for the Internet of Things: A systematic literature review. In Proceedings of the 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA), Agadir, Morocco, 29 November–2 December 2016; pp. 1–6.
• Boudguiga, A.; Bouzerna, N.; Granboulan, L.; Olivereau, A.; Quesnel, F.; Roger, A.; Sirdey, R. Towards better availability and accountability for iot updates by means of a blockchain. In Proceedings of the 2017 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), Paris, France, 26–28 April 2017; pp. 50–58.
• Samaniego, M.; Deters, R. Blockchain as a Service for IoT. In Proceedings of the 2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), Chengdu, China, 15–18 December 2016; pp. 433–436.
• Zhu, C.; Leung, V.C.M.; Shu, L.; Ngai, E.C. Green Internet of Things for Smart World. IEEE Access 2015, 3, 2151–2162.
• Abedin, S.F.; Alam, M.G.R.; Haw, R.; Hong, C.S. A system model for energy efficient green-IoT network. In Proceedings of the 2015 International Conference on Information Networking (ICOIN), Siem Reap, Cambodia, 12–14 January 2015; pp. 177–182.
• Nguyen, D.; Dow, C.; Hwang, S. An Efficient Traffic Congestion Monitoring System on Internet of Vehicles. Wirel. Commun. Mob. Comput. 2018, 2018.
• Namboodiri, V.; Gao, L. Energy-Aware Tag Anticollision Protocols for RFID Systems. IEEE Trans. Mob. Comput. 2010, 9, 44–59.
• ExtraKowsher, M., Tahabilder, A., Sanjid, M. Z. I., Prottasha, N. J., Uddin, M. S., Hossain, M. A., & Jilani, M. A. K. (2021). LSTM-ANN & BiLSTM-ANN: Hybrid deep learning models for enhanced classification accuracy. Procedia Computer Science, 193, 131-140.
• Moon, N. N., Hossain, R. A., Jahan, I., Shakil, S., Uddin, S., Hassan, M., & Nur, F. N. (2022). Predicting the mental health of rural Bangladeshi children in coronavirus disease 2019. International Journal of Electrical and Computer Engineering, 12(5), 5501-10.
• Javed Mehedi Shamrat, F. M., Ghosh, P., Tasnim, Z., Khan, A. A., Uddin, M. S., & Chowdhury, T. R. (2022). Human Face recognition using eigenface, SURF method. In Pervasive Computing and Social Networking: Proceedings of ICPCSN 2021 (pp. 73-88). Springer Singapore.
• Javed Mehedi Shamrat, F. M., Tasnim, Z., Chowdhury, T. R., Shema, R., Uddin, M. S., & Sultana, Z. (2022). Multiple cascading algorithms to evaluate performance of face detection. In Pervasive Computing and Social Networking: Proceedings of ICPCSN 2021 (pp. 89-102). Springer Singapore.
• Hoque, K., Hossain, M. B., Sami, A., Das, D., Kadir, A., & Rahman, M. A. (2024). Technological trends in 5G networks for IoT-enabled smart healthcare: A review. International Journal of Science and Research Archive, 12(2), 1399-1410.
• Maniruzzaman, M., Sami, A., Hoque, R., & Mandal, P. (2024). Pneumonia prediction using deep learning in chest X-ray Images. International Journal of Science and Research Archive, 12(1), 767-773.
• Hasan, A. S. M., & Ibrahim, A. A. (2022, October). Improved WBAN EH_ MAC Protocol based on Energy Harvesting and Wake up-Sleep Duty Cycling Technique. In 2022 International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 478-483). IEEE.
• Fahmudur Rahman, Denesh Das, Anhar Sami, Priya Podder, Daniel Lucky Michael, “Liver cirrhosis prediction using logistic regression, naïve bayes and KNN”, International Journal of Science and Research Archive, 2024, 12(01), 2411–2420.
• Li, T.; Wu, S.S.; Chen, S.; Yang, M.C.K. Generalized Energy-Efficient Algorithms for the RFID Estimation Problem. IEEE/ACM Trans. Netw. 2012, 20, 1978–1990.
• Xu, X.; Gu, L.;Wang, J.; Xing, G.; Cheung, S. Read More with Less: An Adaptive Approach to Energy-Efficient RFID Systems. IEEE J. Sel. Areas Commun. 2011, 29, 1684–1697.
• Klair, D.K.; Chin, K.; Raad, R. A Survey and Tutorial of RFID Anti-Collision Protocols. IEEE Commun. Surv. Tutor. 2010, 12, 400–421.
• Lee, C.; Kim, D.; Kim, J. An Energy Efficient Active RFID Protocol to Avoid Overhearing Problem. IEEE Sens. J. 2014, 14, 15–24.
• Amit Deb Nath, Rahmanul Hoque, Md. Masum Billah, Numair Bin Sharif, Mahmudul Hoque . Distributed Parallel and Cloud Computing: A Review. International Journal of Computer Applications. 186, 16 (Apr 2024), 25-32.
• Imran Hussain Mahdy, Partha Protim Roy and Rafiqul Bari Kabir, “Assessing climate change impacts with downscaling techniques: A case study”, International Journal of Science and Research Archive, 2024, 12(02), 1645–1652.
• Imran Hussain Mahdy, Mujibur Rahman, Fatema Islam Meem and Partha Protim Roy, “Comparative study between observed and numerical downscaled data of surface air temperature”, World Journal of Advanced Research and Reviews, 2024, 23(01), 2019–2034.
• Rahman, M., Ishaque, F., Hossain, M. A., Mahdy, I. H., & Roy, P. P. (2021). Impact of industrialization and urbanization on water quality of Surma River of Sylhet City. Desalination and water treatment, 235, 333-345.