We recently had the opportunity to conduct an exciting Skill Development Program (SDP) at Reva University from 1st April to 4th April 2024. The program was specially organized for 2nd-year Mechanical Engineering students (4th semester), aimed at giving them strong, practical exposure to emerging technologies like Robotics, Internet of Things (IoT), and Machine Learning (ML).
Over the span of four days, students worked on a total of 7 projects, divided in a 2:2:1:2 ratio across the days. The projects were carefully chosen to balance both software and hardware understanding. The projects covered were:
- Obstacle Avoider Robot
- Light Seeking Robot
- Voice Controlled Robot
- Object Recognizer Robot
- Temperature and Humidity Detection System using IoT and ML
- Water Leakage Monitoring System with Live Data Monitoring using IoT and ML
- Machine Vibration Monitoring System for Predictive Maintenance using IoT and ML
The first four projects focused primarily on Robotics, where students programmed robots to interact intelligently with their environment. We used MicroPython as the primary programming language for these projects, providing students with a simple yet powerful platform to learn embedded programming concepts. For the final project on predictive maintenance, Arduino programming was introduced to control and manage hardware operations at a deeper level.
For the IoT and ML-based systems, students were introduced to powerful platforms like Dockers and ThingsBoard, enabling them to perform live data monitoring and analysis. This provided them with firsthand experience in setting up servers, managing device communication, and visualizing sensor data on live dashboards. It was a great way for them to connect theoretical knowledge with real-world applications.
An important highlight of the workshop was the live testing sessions. For the Water Leakage Monitoring System, we physically passed water through the system and monitored the flow rate in real time, allowing students to validate their models. Similarly, for the Machine Vibration Monitoring System, we used a wear testing machine to generate vibrations and successfully demonstrated predictive maintenance concepts by analyzing real-time vibration data.
Throughout the program, various sensors like piezoelectric sensors, water pressure sensors, and obstacle detection sensors were integrated into projects. Students learned how to connect, program, and calibrate these sensors, gaining in-depth knowledge of both hardware interfacing and software development.
Overall, the Student Development Program was a tremendous success. The students not only built and programmed multiple real-world projects but also gained invaluable exposure to essential industry technologies. By the end of the workshop, they had a strong understanding of integrating hardware and software, real-time monitoring systems, and predictive maintenance models — critical skills that will give them a strong advantage in their future careers.