MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641115049 A) filed by Dr. S M Deepa; Raju Chitla; Bharani Maroju; Dr T Jayaprakash; Mr. S Ahamed; Mr. A Harishpandi; Mr. K Karventhan; and Mr. B Lokesh on September 25, 2026, for Smart Energy Management And Load Scheduling With Solar Integration.
Inventors include Dr. S M Deepa; Raju Chitla; Bharani Maroju; Dr T Jayaprakash; Mr. S Ahamed; Mr. A Harishpandi; Mr. K Karventhan; and Mr. B Lokesh.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: An AI-enabled, IoT-based real-time energy management and smart load scheduling system is disclosed, built around a Raspberry Pi 3 Model B+ operating as a central controller. The system continuously monitors electrical parameters through voltage and current sensors and environmental conditions through a DHT11 sensor, while simultaneously tracking battery state of charge. Sensor data is processed through a two-tier decision architecture: a deterministic safety layer that instantly disconnects loads via a relay module and triggers a buzzer alert upon detecting overvoltage, overcurrent, or over-temperature conditions, and an artificial-intelligence-based scheduling layer that forecasts load demand and solar generation to optimise the timing of deferrable loads. Loads are classified into critical, essential, and deferrable priority classes and are automatically shed or restored as battery charge crosses predefined thresholds, with hysteresis preventing relay chattering. A solar panel and rechargeable battery provide continuous, grid-independent power to both the controller and connected loads, while a wireless interface logs data locally and transmits it to a cloud-based dashboard for real-time monitoring and manual override. The system's machine-learning model is periodically retrained on accumulated historical data, allowing its scheduling behaviour to adapt to the specific usage pattern of the installation over time. By integrating real-time sensing, fail-safe protection, predictive scheduling, and renewable backup within a single low-cost embedded platform, the invention significantly reduces energy wastage, extends battery life, and improves the reliability and automation of energy management for residential, agricultural, and off-grid smart energy applications.
Disclaimer: Curated by HT Syndication.
