IOT Based Smart Energy Efficient System for Next Generation House

Abstract

Developing the quotAction Immediate Response on Home Entry Point (AIRonHEP)quot newlinesystem introduces a pioneering approach to smart home automation and security. This newlineinnovative gateway utilizes Internet of Things (IoT) technologies to enhance the newlineresponsiveness and efficiency of smart home environments, catering to the evolving newlineneeds of modern urban living. By integrating advanced sensor technologies and IoT newlineconnectivity, the AIRonHEP system provides a robust solution for managing home newlineentry points with heightened security and improved energy management. newlineCentral to this research is the design and implementation of two multi-user gateways newlinethat operate on a layered architecture level, each meticulously detailed with device newlinespecifications to ensure cost efficiency and functional efficacy. The AIRonHEP newlinesystem is distinguished by its dual-mode operation, which allows for manual user newlinecontrol and automatic responses based on predefined user settings. This feature is newlineessential for maintaining flexibility and user-centricity while supporting autonomous newlineoperation when necessary. newlineThe AIRonHEP system has significantly improved over traditional ZigBee and other newlineIoT-based systems through comprehensive simulations and real-world applications. It newlinenotably enhances range coverage supporting up to 20 kilometres point-to-point and 2 newlinekilometres locally while providing a safer, more reliable, cost-effective solution. newlineThese attributes make it particularly suitable for the expansive requirements of smart newlinecities and industries seeking to integrate scalable, intelligent technologies. Future newlineenhancements of the AIRonHEP system will focus on integrating Very Large Scale newlineIntegration (VLSI) to reduce the physical footprint and power consumption, further newlinebolstering its applicability in global smart home markets. Additionally, incorporating newlinemachine learning algorithms for improved security measures represents a critical area newlinefor development, aiming to fortify defences against increasingly sophisticated cyber newlinethreats. This research lays the groundwork f