IRHA：一种基于智能RSSI的家庭自动化系统
IRHA: An Intelligent RSSI based Home automation System
摘要：
由于自动化领域的显着进步，人类的生活在许多领域变得越来越复杂和更好。在当前环境下，自动化系统比手动系统更受青睐。家庭自动化在这种情况下变得越来越流行，因为人们被可以自动满足用户需求的家庭环境的概念所吸引。智能家居面临的主要挑战是智能决策，位置感知服务以及不同年龄和身体状况的所有用户的兼容性。现有的解决方案仅解决了其中的一两个挑战，但需要强大、智能、位置感知和预测的灵巧家庭自动化来满足用户的需求。本文提出了一种基于RSSI的位置感知智能家庭自动化系统（IRHA），该系统使用Wi-Fi信号来检测用户的位置并自动控制电器。指纹识别方法用于映射不同房间的Wi-Fi信号，并且机器学习方法（诸如决策树）用于对不同房间的信号进行分类。然后在ESP 32微控制器板中实现机器学习模型，以根据实时Wi-Fi信号对房间进行分类，然后通过ESP 32 MAC通信协议将结果发送到主控制板，以自动控制电器。所提出的方法在分类用户的位置时达到了97%的准确率。
英文摘要：
Human existence is getting more sophisticated and better in many areas due to remarkable advances in the fields of automation. Automated systems are favored over manual ones in the current environment. Home Automation is becoming more popular in this scenario, as people are drawn to the concept of a home environment that can automatically satisfy users' requirements. The key challenges in an intelligent home are intelligent decision making, location-aware service, and compatibility for all users of different ages and physical conditions. Existing solutions address just one or two of these challenges, but smart home automation that is robust, intelligent, location-aware, and predictive is needed to satisfy the user's demand. This paper presents a location-aware intelligent RSSI-based home automation system (IRHA) that uses Wi-Fi signals to detect the user's location and control the appliances automatically. The fingerprinting method is used to map the Wi-Fi signals for different rooms, and the machine learning method, such as Decision Tree, is used to classify the signals for different rooms. The machine learning models are then implemented in the ESP32 microcontroller board to classify the rooms based on the real-time Wi-Fi signal, and then the result is sent to the main control board through the ESP32 MAC communication protocol to control the appliances automatically. The proposed method has achieved 97% accuracy in classifying the users' location.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
