EcoSMEAL: Energy Consumption with Optimization Strategy via a Secured Smart Monitor-Alert Ensemble

Tabitha Chukwudi Aghaunor (Robert Morris University)
Joy Agboi (Delta State University)
Eferhire Valentine Ugbotu (University of Salford)
Paul Avweresuoghene Onoma (Federal University of Petroleum Resources Effurun)
Arnold Adimabua Ojugo (Federal University of Petroleum Resources Effurun)
Christopher Chukwufunaya Odiakaose (Dennis Osadebay University)
Andrew Okonji Eboka (Federal College of Education (Technical))
Peace Oguguo Ezzeh (Federal College of Education (Technical))
Victor Ochuko Geteloma (Federal University of Petroleum Resources Effurun)
Amaka Patience Binitie (Federal College of Education (Technical))
Anderson Ise Orobor (Federal University of Petroleum Resources Effurun)
Blessing Uche Nwozor (Federal University of Petroleum Resources Effurun)
Patrick Ogholuwarami Ejeh (Dennis Osadebay University Asaba)
Christopher Chukwudi Onochie (Federal College of Education (Technical))

Journal of Fuzzy Systems and Control (JFSC)
Vol. 3 No. 3 (2025): Vol. 3 No. 3 (2025)

The global demand for automation that seeks the efficient consumption and usage of energy via the adoption of embedded-fit management solutions that yield improved performance with reduced consumption has become the new norm. These explore sensor-based units in their own right with eco-friendly platforms that raise germane environmental, health, and consumption regulation(s) concerns that have today become a global issue, even when they proffer improved life standards that replace traditional solutions. Our study posits an embedded sensor design to observe environmental conditions associated with energy consumption by residential or home appliances. It utilizes a machine learning scheme and algorithm to analyze the total energy consumed by each appliance and delivers optimal consumption that reduces energy waste. The system was tested across multiple parameters and found to yield desired effectiveness, reliability, and efficiency. Our utilization of the ESP8266 and ThingSpeak is able to handle extensive inputs without significant delays or data losses. Results affirms the system ability to maintain stable performance even with more devices connected to the unit.