Jun 2026· BIMA JOURNAL OF SCIENCE AND TECHNOLOGY GOMBE· Vol 10, pp. 193-208· 0 citations
TL;DR
The design and execution of a low-cost, locally adjustable smart energy monitoring and load control system for residential and small-scale industrial applications and the results show that low-cost IoT-based devices can improve energy efficiency, cut expenses.
Abstract
Energy supply is constantly becoming unstable, inefficient, and expensive due to the exorbitant cost of imported smart meters, which prevents their widespread use. The design and execution of a low-cost, locally adjustable smart energy monitoring and load control system for residential and small-scale industrial applications are presented in this paper. To provide real-time monitoring and intelligent load control, the system combines an Arduino-based Internet of Things platform with voltage and current sensors, relay modules, and cloud-based visualization. Over the course of 30 days, the prototype was installed in three homes with various load profiles after being calibrated against standard meters. Through a mobile dashboard, the solution effectively reduced wasteful consumption, enhanced user awareness, and automated load prioritization during periods of high demand. The obtained energy reductions are competitive with global standards while maintaining noticeably reduced costs through local hardware sourcing. Although Wi-Fi instability and sporadic resets following power surges were issues, user comments validated the ease of use. The results show that low-cost IoT-based devices can improve energy efficiency, cut expenses.
Traditional energy management at universities is characterised by manual monitoring, static control systems, and lack of real-time data, resulting in excessive energy consumption and high operational costs. This study presents the design, implementation, and evaluation of a Smart Energy Management System (SEMS) at the University of Calabar, Cross River State, Nigeria, with the objective of reducing energy consumption and operational costs. The SEMS integrates Internet of Things (IoT) sensors, real-time data analytics, and automated control mechanisms to monitor and manage energy consumption dynamically. Key hardware components include motion sensors, smart meters, and environmental monitors, all connected to a centralised dashboard that provides actionable insights for energy optimisation. A six-month pilot deployment using a three-tier IoT architecture demonstrated energy savings of 30–40%, improved operational efficiency, with automated response times of 2–4 seconds and system uptime exceeding 95%. Comparative analysis confirmed that the SEMS outperforms traditional energy management in responsiveness (automated response time of 2.5–3.5 seconds versus delayed manual response), cost-effectiveness (30–40% reduction in energy expenditure with low long-term operational costs), and data visibility (real-time, room-level consumption data versus monthly, incomplete utility bills). The study provides a scalable framework for implementing smart energy solutions in university settings.
Ofem Ajah Ofem, Iniobong Ime, Osowomuabe Njama-Abang et al.· Global Journal of Pure and A...· 0 citations
IoT is one of the significant enabling technologies in the contemporary energy landscape. This work addresses intelligent load management under fault, under-load, and overload conditions. Electrical equipment requires automatic and rapid response to avoid damage and prevent service interruption. In contrast to traditional circuit breakers that disconnect the entire system, the proposed architecture employs ESP32-based intelligent control, together with ACS712 current sensors, to provide accurate per-load current measurements and load-specific overcurrent protection. The system is also capable of selective load isolation, meaning that it maintains the operation of healthy circuits and automatically disconnects only the faulty load without affecting other loads. Cloud-based monitoring is implemented via the ThingSpeak platform, enabling real-time remote system surveillance through any internet-connected device. The faulty section of the system is readily identified from the current readings visualised on the cloud dashboard and mobile interface. The proposed system is powered primarily by solar photovoltaic sources and can also operate from the utility grid, providing flexibility across renewable and conventional supply scenarios. Experimental testing demonstrates protection response times in the sub-200 ms range and high-accuracy current monitoring with a mean absolute error below 0.05 A. The key contributions include: selective load protection, real-time IoT-based energy analysis, and a cost-effective open-hardware architecture. The work advances the safety and efficiency of smart energy control systems in distributed renewable energy environments.
Jeevitha Kandasamy, Kalaivani C, Shashank S Bhagwat et al.· 2026 4th International Confe...· 0 citations
The rapid growth in electricity consumption has increased the need for intelligent energy management and protection systems. Conventional electrical monitoring systems lack real-time analysis and remote accessibility, leading to energy wastage and delayed fault response. This paper presents a Smart Energy Optimization and Protection System using Internet of Things (IoT) technology for efficient monitoring, fault detection, and energy management. The proposed system continuously monitors electrical parameters such as voltage, current, and power consumption using sensors interfaced with an embedded controller. The collected data is transmitted to a cloud platform through IoT connectivity, enabling real-time monitoring and remote access through mobile or web applications. The system identifies abnormal conditions such as overload, short circuit, over-voltage, and excessive energy consumption using threshold-based analysis. Upon detecting faults, immediate alerts and protection mechanisms are activated to prevent equipment damage and improve system safety. Additionally, the system provides energy optimization suggestions to reduce unnecessary power consumption. The integration of IoT enhances system scalability, accessibility, and efficiency, making the proposed model suitable for residential, commercial, and industrial applications.,
K. Thamizhazhakan, D. Vinoth, S. Bharanivelan et al.· 2026 6th International Confe...· 0 citations
The increasing need of a sustainable energy means that smaller grid friendly and intelligent systems are needed that can effectively handle renewable energy. Traditional renewable installations usually need much space, are associated with a high price and lack easy incorporation with smart control and real-time monitoring systems. In this paper, the author introduces the development of a small smart renewable energy control platform comprising of solar energy collection, intelligent control and IoT-based monitoring. The system consists of the voltage regulation DC to DC converter, a battery storage, and the main controller is an Arduino Uno (ATmega328P). Total measurements are an environmental and electrical parameter with DHT11, voltage and current sensors. A local monitoring is available on an LCD whereas an ESP32 can allow connectivity to the cloud where real-time uses of an IoT can be realized. Relay drivers are used to provide automated load control and electronic grid switching. Its effectiveness and scalability 92% conversion efficiency, voltage stability (in the range of ±2%), and response time (less than 150 ms) have been proven by experimental results.
Harshavardan M, Anbu Selvam M, B. V· International Conference Com...· 0 citations
The increasing complexity of residential energy systems and the growing penetration of distributed resources require practical energy-management solutions that extend beyond conventional metering. This paper presents the design and implementation of a real-time Internet of Things (IoT)-based energy-management system for monitoring and controlling household energy consumption under different operating conditions. The proposed system adopts a dual-processor architecture, in which a primary microcontroller performs time-critical electrical measurements and low-level load switching, while a secondary processor operates as a local IoT gateway for data handling, rule-based control decisions, local visualization, and message queuing telemetry transport (MQTT)-based cloud communication through a 4G link. The contribution of this work is not associated with the individual use of dual processing, cellular communication, cloud monitoring, load shedding, or backup power, as these technologies have been previously reported in smart-metering and home energy-management systems. Instead, the study focuses on their coordinated integration within a residential-scale prototype that combines calibrated per-load monitoring, priority-based load control, outage-resilient reporting, and credit-aware load restriction. The system measures voltage, current, active and apparent power, power factor, and energy consumption for individual loads and supports centralized visualization through a cloud-based dashboard. The prototype was experimentally evaluated under three representative scenarios: overload, main power outage, and low-credit operation. In the overload scenario, automatic priority-based load shedding reduced the total load by up to 75%. During power outages, a battery-supported subsystem maintained monitoring and communication for real-time outage reporting. In the low-credit scenario, non-essential loads were disconnected when the user balance fell below a predefined threshold, while essential loads remained energized. The results demonstrate that the implemented prototype can provide integrated monitoring, local rule-based control, cloud reporting, and backup-supported operation within a unified residential energy-management platform.
Mohammed Sabah, Akram Elmitwally, A. Eladl· Engineer· 0 citations
The increasing demand for renewable energy has highlighted the need for efficient and reliable management of solar power plants. Solar plants, whether residential or industrial, require continuous monitoring to ensure optimal performance, detect faults, and maximize energy generation. Manual supervision is often time-consuming, prone to errors, and insufficient for detecting real-time anomalies. To address these challenges, this paper presents an IoT-based Solar Plant Monitoring System that enables remote, real-time observation and management of solar energy systems. The proposed system integrates sensors, microcontrollers, and IoT-enabled communication modules to collect key parameters such as solar panel voltage, current, temperature, and battery status. These parameters are transmitted over the internet to a centralized cloud platform, allowing plant operators to monitor system performance from any location using smartphones, laptops, or tablets. Alerts are generated automatically in case of abnormal readings, such as low voltage, panel overheating, or battery faults, facilitating proactive maintenance and minimizing downtime. By leveraging IoT technology, the system not only improves the efficiency and reliability of solar power generation but also reduces operational and maintenance costs. The proposed system supports data logging, historical analysis, and performance optimization. Additionally, the integration of cloud-based monitoring ensures scalability and flexibility, allowing expansion to multiple solar plants and large-scale installations.
S. S., A. S, D. K. et al.· International Conference Com...· 0 citations
