The Department of Statistics and Data Science organised a two-day hands-on workshop on the Internet of Things (IoT) for MSc Data Science students on 7 and 8 September 2026. The sessions were conducted from 8:00 AM to 12:45 PM and were led by Dr. Alwin Joseph. The workshop aimed to introduce students to the fundamental components of IoT systems and provide practical experience in connecting sensors, programming devices and transmitting data through wireless networks.
The first day began with an introduction to the basic components commonly used in IoT applications. Students were familiarised with sensors, breadboards, Arduino boards, LEDs and buzzers. The resource person explained the purpose of each component and demonstrated how they could be connected to create a functional electronic circuit.
The first practical activity involved connecting an LED to an Arduino using a breadboard and programming it to light up. Students then progressed to activities involving buzzers and sensors. These exercises helped them understand how a device can receive information from its surroundings and generate an appropriate output.
A major activity conducted during the first day focused on distance detection. Students used a sensor to identify the distance of an object and programmed the system to respond differently according to its proximity. When the object was detected within five centimetres, a red LED blinked and the buzzer produced an alert. A green LED was activated when the object was within ten centimetres, while a yellow LED indicated the subsequent distance range. This activity demonstrated the integration of sensors, programming and output devices in a practical IoT system.
The second day focused on the NodeMCU ESP8266, a microcontroller board with built-in Wi-Fi capability. Students learned how to connect the board to a computer and configure it using the Arduino development environment. They subsequently connected sound, light and temperature sensors to the board. A buzzer and an LCD display were also integrated into the system to provide alerts and display the information collected by the sensors.
The sound sensor was used to detect sound, the light sensor measured the surrounding light level, and the temperature sensor provided temperature readings. Students then explored how the built-in Wi-Fi capability of the NodeMCU could be used to transmit the collected sensor data to a computer.
A Python Flask application was prepared to receive the data transmitted by the NodeMCU through Wi-Fi. Students were also introduced to the basic setup of a web-based IoT dashboard for displaying information such as temperature readings, light levels and sound status. During the practical activities, hardware, configuration and communication-related issues were identified and examined, providing students with a realistic understanding of the challenges involved in implementing an IoT system.
The workshop enabled students to progress from creating a basic LED circuit to working with a Wi-Fi-enabled sensor-monitoring system. By integrating electronic components, sensors, programming, wireless communication and data display, the workshop provided an effective introduction to the functioning of IoT applications. It also demonstrated the connection between IoT and data science, particularly in the collection, transmission and presentation of real-time data.
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