Diagnostic Machine safety with IoT Monitoring

After analyzing the current situation of safety of diagnostic machine, it is realized that there is a need to develop a system that could inform the users about various faults in the machine, thereby protecting from severe damages. The proposed project presents a novel system that monitors machines and detects faults. This project is a model for a real time monitoring system using contemporary technologies like Internet of Things (IoT)-based sensors that are promising for efficient machine monitoring. The proposed project is a model for a real-time monitoring system using IoT-based sensors accessible via webpages. The system involves connecting the machine to two sensors: a current sensor to continuously monitor current flow and a temperature sensor to gauge heat production. These sensors provide input signals to an Arduino controller, which processes them into real values based on sensor output electrical signals. Subsequently, these values are translated from machine-level language to low-level language and displayed on an LCD. A Wi-Fi module facilitates transmission of these values over the internet to cloud storage. In this system "ThingSpeak" is opted as cloud platform, offering data collection. This platform stores the data, enabling access to values worldwide via webpages. It also generates graphs depicting sensor values over time. Key Words: Fault detection, Machinery monitoring, Arduino controller, Cloud storage, Real-time monitoring