We see the trends of students embarking on IoT projects as their Group project assignments or Final Year Projects (FYP). It is a positive move in preparing the talents of the future. The industry is hungry for new skills readily equipped with the knowledge to innovate and develop innovative solutions.
However, we need to resolve several issues to ensure students would not fail to deliver the project.
Four Critical Problems
- An incomplete IoT Lab – Most experiments only focus on standalone Arduino or Raspberry Pi devices without connecting to an IoT platform or sending data to the cloud. Thus, the lack of understanding of using an IoT middleware and learning different protocols such as REST, CoAP, and MQTT.
- Too many to choose – Students have to research hundreds of IoT middleware before choosing one for their Final Year projects.
- Limited time – Students cannot complete IoT projects on time because they are busy developing their own “middleware” or Database or troubleshooting the connectivity between the sensor device and the server.
- Software and Hardware Skills – Students in engineering can be good in hardware but lack software programming skills. But students in IT or Computer Science can be good in Software Programming but lack the skills in building hardware electronics. IoT requires skills or a good understanding of both hardware and software.
We recommended that the universities cover these critical components in their courses to prepare the students to take IoT as their Final Year Projects.Four (4) Tips That Will Help Universities to Prepare Their IoT Education Click To Tweet
Four (4) Tips That Will Help Universities to Prepare
- Learn the 7-Layers of OSI (Open System Interconnection) – Cover this as early as possible and understand how all the seven layers interact and how the rest of the subjects relate to 7-layers.
- If not 7, Learn at least the 4-Layers – 4 critical components are made up of the Internet of Things and must be taught more detail. They are (i) Sensors, (2) Connectivity, (3) IoT platforms or middleware (4) Applications.
- Fully equipped Lab – As per item (2), the student must undergo the whole process of learning how to build or connect sensors to a microprocessor. Learn how to send data to an IoT platform using simple Bluetooth, Zigbee, or WiFi. More complex connectivity options would be LoRa or SigFox, or NB-IoT. A complete understanding of using REST, CoAP, or MQTT from a device to an IoT platform. And finally, using a web-based or mobile app to create a dashboard. A more advanced Lab will comprise machine learning or big data analytics experiments.
- Update the Lecturers’ skills – New technology requires new skills, and the lecturers need to upgrade their skills. Especially using new tools in the market is essential to prepare the student for the industry.
Today, the industry doesn’t have time to send the students for training when they join the company. They expect the students to understand the basics and immediately start a project or join an existing team.
What other factors did you think might hinder the university’s project success? Please leave your comments below.