Open Access

ARTICLE

Low Cost Autonomous Learning and Advising Smart Home Automation System

Daniel Chioran^*, Honoriu Valean

Department of Automation, Technical University of Cluj Napoca, Cluj Napoca, 400114, Romania

* Corresponding Author: Daniel Chioran. Email:

Intelligent Automation & Soft Computing 2022, 31(3), 1939-1952. https://doi.org/10.32604/iasc.2022.020649

Received 01 June 2021; Accepted 22 July 2021; Issue published 09 October 2021

Abstract

In today’s world, more than ever before, we are fascinated and drawn towards smart autonomous devices that make our lives safer and more comfortable. Devices that aid in reducing our energy consumption are also highly appreciated but often quite expensive to buy. This context is favorable for developing an autonomous smart home automation system (SHAS) with energy-saving potential and low price, making it widely accessible. This paper presents the design and prototype implementation of such a low-cost micro-controller based autonomous SHAS that learns the resident’s work schedule and integrates a wide array of sensors and actuators to automatically control the lights, temperature, humidity and power sockets. The proposed automation system also monitors the home environment for potential energy-saving opportunities, gas leaks, or unauthorized entry. For reliability purposes and to limit the risk of signal interference, the proposed system design uses a wired inter-module communication method. To enhance the home’s security, both personal identification number (PIN) protection and Global System for Mobile Communications (GSM) communication are added, making the proposed system design less vulnerable to cyber-attacks when compared to other wireless alternatives. The hardware and software architectures, the prototype test results and the cost analysis are presented in detail, validating the system’s design and efficient operation as an autonomous smart home automation system.

---

Keywords

---