Maintenance Scheduling of Heavy Machinery Using IoT for Wide Range of Real-Time Applications

This proposed system presents the design of machinery maintenance scheduling system using Twitter feed with the use of ARM processor FRDMKL25Z, cloud service “ThingSpeak” and ESP8266 Wi-Fi module. The sensors in the system intensively monitor temperature, vibrations and smoke in the machinery. Measured parameters from sensors are sent to cloud for analysis through Wi-Fi module by the processor to monitor the data continuously. When the sensor data crosses certain safety level in the machinery, then an alert notification is sent to the Twitter feed. The sensor data is continuously monitored by the processor and is stored in the cloud service “ThingSpeak” which analyzes the data. When the data crosses certain safety levels, then a live Twitter feed notification is updated to the linked organizational Twitter account. We can also set a reminder for machinery service by giving date and time to ThingSpeak.