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@article{206816,
        author = {Suham Nagekar and Gourish Hegde and Rajesh M and Rakesh S K and Suntosh R V},
        title = {IoT Based Smart Energy System for Apartments},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {555-559},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206816},
        abstract = {Energy consumption in residential buildings has been increasing rapidly due to the rising use of electrical appliances and inefficient monitoring practices. Many apartment residents are unaware of their daily electricity usage, which often leads to unexpected high bills and wastage of energy. To address this problem, the IoT-Based Smart Energy Monitoring System for Apartments is designed to provide real-time tracking, analysis, and notification of energy consumption at the device level. This system helps users understand their electricity usage patterns, identify power hungry appliances, and take timely corrective actions to reduce energy wastage.
The system uses a NodeMCU (ESP32) with ACS712 sensors to monitor appliance energy consumption in real time, displaying data locally on an OLED and sending it to platforms like Blynk and ThingSpeak for visualization and storage. It also alerts users when usage exceeds 150 units, offering an affordable, scalable solution that promotes energy efficiency, cost savings, and smart home awareness.},
        keywords = {Edge AI, EMNIST dataset, Jetson Nano, Leaky Integrate-and-Fire neuron, neuromorphic computing, spiking neural networks, temporal coding.},
        month = {July},
        }