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Optimizing IoT Energy Efficiency: Real-Time Adaptive Algorithms for Smart Meters with LoRaWAN and NB-IoT

Author

Listed:
  • Kanar Alaa Al-Sammak

    (Faculty of Electronics, Telecommunications and Information Technology, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania)

  • Sama Hussein Al-Gburi

    (Faculty of Electronics, Telecommunications and Information Technology, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania)

  • Ion Marghescu

    (Faculty of Electronics, Telecommunications and Information Technology, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania)

  • Ana-Maria Claudia Drăgulinescu

    (Faculty of Electronics, Telecommunications and Information Technology, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania)

  • Cristina Marghescu

    (Faculty of Electronics, Telecommunications and Information Technology, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania)

  • Alexandru Martian

    (Faculty of Electronics, Telecommunications and Information Technology, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania)

  • Nawar Alaa Hussein Al-Sammak

    (College of Education for Pure Science, University of Kerbala, Babylon 56001, Iraq)

  • George Suciu

    (Faculty of Electronics, Telecommunications and Information Technology, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
    BEIA Consult International, 060042 Bucharest, Romania)

  • Khattab M. Ali Alheeti

    (College of Computer Science and Information Technology, University of Anbar, Ramadi 31001, Iraq)

Abstract

Real-time monitoring, data-driven decisions, and energy consumption optimization have reached a new level with IoT advancement. However, a significant challenge faced by intelligent nodes and IoT applications resides in their energy requirements in the long term, especially in the case of gas or water smart meters. This article proposes an algorithm for smart meters’ energy consumption optimization based on IoT, LoRaWAN, and NB-IoT using microcontroller-based development boards, PZEM004T energy meters, Dragino LoRaWAN shield, or BG96 NB-IoT modules. The algorithm adjusts the transmission time based on the change in data in real-time. According to the experimental results, the energy consumption and the number of packets transmitted significantly decreased using LoRaWAN or NB-IoT, saving up to 76.11% and 86.81% of the transmitted packets, respectively. Additionally, the outcome highlights a notable percentage reduction in the energy consumption spike frequency, with NB-IoT achieving an 87.3% reduction and LoRaWAN slightly higher at 88.5%. This study shows that adaptive algorithms are very effective in extending the lifetime of IoT nodes, thereby providing a solid baseline for scalable, lightweight, energy-monitoring IoT applications. The results could help shape the development of smart energy metering systems and sustainable IoT.

Suggested Citation

  • Kanar Alaa Al-Sammak & Sama Hussein Al-Gburi & Ion Marghescu & Ana-Maria Claudia Drăgulinescu & Cristina Marghescu & Alexandru Martian & Nawar Alaa Hussein Al-Sammak & George Suciu & Khattab M. Ali Al, 2025. "Optimizing IoT Energy Efficiency: Real-Time Adaptive Algorithms for Smart Meters with LoRaWAN and NB-IoT," Energies, MDPI, vol. 18(4), pages 1-33, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:4:p:987-:d:1593907
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    References listed on IDEAS

    as
    1. Mohammad Mansour & Amal Gamal & Ahmed I. Ahmed & Lobna A. Said & Abdelmoniem Elbaz & Norbert Herencsar & Ahmed Soltan, 2023. "Internet of Things: A Comprehensive Overview on Protocols, Architectures, Technologies, Simulation Tools, and Future Directions," Energies, MDPI, vol. 16(8), pages 1-39, April.
    2. Yousaf Murtaza Rind & Muhammad Haseeb Raza & Muhammad Zubair & Muhammad Qasim Mehmood & Yehia Massoud, 2023. "Smart Energy Meters for Smart Grids, an Internet of Things Perspective," Energies, MDPI, vol. 16(4), pages 1-35, February.
    3. Silva, Jéssica Alice A. & López, Juan Camilo & Guzman, Cindy Paola & Arias, Nataly Bañol & Rider, Marcos J. & da Silva, Luiz C.P., 2023. "An IoT-based energy management system for AC microgrids with grid and security constraints," Applied Energy, Elsevier, vol. 337(C).
    4. Hafiz Abdul Muqeet & Rehan Liaqat & Mohsin Jamil & Asharf Ali Khan, 2023. "A State-of-the-Art Review of Smart Energy Systems and Their Management in a Smart Grid Environment," Energies, MDPI, vol. 16(1), pages 1-23, January.
    5. Priyanka Mishra & Ghanshyam Singh, 2023. "Energy Management Systems in Sustainable Smart Cities Based on the Internet of Energy: A Technical Review," Energies, MDPI, vol. 16(19), pages 1-36, September.
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