Version 1
: Received: 18 June 2024 / Approved: 19 June 2024 / Online: 19 June 2024 (16:41:35 CEST)
How to cite:
Khan, R.; Khan, D. Smart Presence Detection: Harnessing Wi-Fi Signals and Machine Learning with ESP8266. Preprints2024, 2024061346. https://doi.org/10.20944/preprints202406.1346.v1
Khan, R.; Khan, D. Smart Presence Detection: Harnessing Wi-Fi Signals and Machine Learning with ESP8266. Preprints 2024, 2024061346. https://doi.org/10.20944/preprints202406.1346.v1
Khan, R.; Khan, D. Smart Presence Detection: Harnessing Wi-Fi Signals and Machine Learning with ESP8266. Preprints2024, 2024061346. https://doi.org/10.20944/preprints202406.1346.v1
APA Style
Khan, R., & Khan, D. (2024). Smart Presence Detection: Harnessing Wi-Fi Signals and Machine Learning with ESP8266. Preprints. https://doi.org/10.20944/preprints202406.1346.v1
Chicago/Turabian Style
Khan, R. and Danish Khan. 2024 "Smart Presence Detection: Harnessing Wi-Fi Signals and Machine Learning with ESP8266" Preprints. https://doi.org/10.20944/preprints202406.1346.v1
Abstract
Presence detection is essential in many applications, including smart homes, office automation, and public space management. Traditional technologies like infrared sensors and cameras frequently encounter obstacles due to privacy concerns, high costs, and complexity. The study provides a novel way to detect presence based on Wi-Fi signals and machine learning algorithms, utilizing the ESP8266 microcontroller. The suggested system attempts to reliably detect the presence of people in a given place by evaluating fluctuations in Wi-Fi signal strength and patterns. The theoretical basis of this strategy is investigated, including the ESP8266’s capabilities for Wi-Fi data gathering and the use of machine learning methods for data analysis. The methodology includes data collecting with the ESP8266, preprocessing, feature extraction, and training and evaluating machine learning models. This system’s potential uses include smart home automation, office occupancy tracking, and crowd management in public settings. The paper also discusses potential issues such as signal interference, data privacy concerns, and the limitations of Wi-Fi detection. Future work is also mentioned, including the suggested system’s installation and testing and enhancement proposals to improve accuracy and scalability. This research aims to provide a cost-effective, non-intrusive, and scalable presence detection system by harnessing the power of Wi-Fi signals and machine learning, enhancing intelligent environments
Keywords
Presence Detection; Wi-Fi Signals; ESP8266; Signal Interference; Smart home automation
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.