IOT- Based Overweight Preventer Using ESP3266 and HX711
A M Shanmugapriya
Department of ECE, UG Student
KGiSL Institute of Technology
Coimbatore,Tamilnadu,India
chandrupriya311@gmail.com
R Sindhu
Department of ECE, UG Student
KGiSL Institute of Technology
Coimbatore,Tamilnadu,India
sinram200440@gmail.com
S V K Deepika Priya
Department of ECE, Assistant rofessor
KGiSL Institute of Technology
Coimbatore,Tamlnadu,India
svkdeepika@gmail.com
K Yokesh
Department of ECE, UG Student
KGiSL Institute of Technology
Coimbatore,Tamlnadu,India
yokesh73396@gmail.com
Abstract— The Internet of Things (IoT) has transformed multiple sectors by enabling real-time data acquisition, remote monitoring, and intelligent automation. This paper presents the design and implementation of an IoT-based overweight preventer system aimed at improving safety, operational efficiency, and proactive load management in various weight-sensitive applications. The system is built around the ESP8266 microcontroller, chosen for its low power consumption and built-in Wi-Fi capabilities, and the HX711 load cell amplifier, which ensures precise and accurate weight measurement The proposed system continuously monitors weight through a calibrated load cell, processes the data in real-time using the ESP8266, and transmits the collected information to a remote web server via Wi-Fi. The server hosts an intuitive user interface that allows for real-time weight tracking, historical data logging, and automated alerts when weight thresholds are exceeded. Though initially targeted at orthopedic healthcare—such as monitoring patient weight during post-surgical recovery—the system’s architecture is modular and applicable in various domains including vehicle load monitoring, industrial weighing systems, smart agriculture, and inventory management. Preliminary testing demonstrates high accuracy, low latency, and reliable connectivity, proving the system's potential as a scalable, cost-effective solution. Future enhancements include integration with mobile applications, machine learning algorithms for predictive insights, and multi-sensor network support.
Keywords— IoT, ESP8266, HX711, Load Cell, Real-Time Monitoring, Weight Management, Overweight Detection, Remote Sensing, Web Server, Orthopedic Applications.
