The team at IoT Sources is constantly on the lookout for innovative IoT use cases. Recently, we found a use case associated with higher education and research that involves the Internet of Things (IoT), artificial intelligence (AI) and machine learning (ML) plus a little virtual reality VR.

The intersection of these four technology innovations fits perfectly to the digital transformation needs of higher education and research considering the data-intensive aspects of the industry. It also enables the industry to leverage the cost efficiency aspects of the IoT to help control and reduce operational costs for facilities, classroom occupancy, and energy consumption.

The Internet of Things and the three other forward-looking technologies enable universities and colleges to create immersive educational spaces with integrated virtual-reality environments for smarter learning. Imagine trade schools using VR for hands-on training without the carrying costs and necessary space for physical machinery? Likewise, biology, physiology, chemistry and other sciences exploring the human body and nature through VR?

Froma research perspective, clearly machine learning, and AI have significant applications. The speed though of data analysis and predictive insights will enable universities to become agiler for serving both the public and private markets.

Additional ways in which the IoT, AI, ML, and VR are transforming higher education and research include:

  • Immersive and connected educational spaces
  • Smarter classrooms
  • Safer campuses through environmental monitoring and controlled access
  • Connected infrastructure: Safer, more efficient use of space and occupancy
  • Increased sustainability and cost savings for energy consumption
  • AI-powered research

An article in explained another IoT application for higher education and research,

Through the use of smart technologies, universities are also able to design personalised learning solutions according to the needs of individual students. Information can be automatically gathered about students and their use of learning resources, AI and ML can be integrated for the system to learn and adapt. Smart technologies can also be included in the system to help generate different learning scenarios according to the students’ needs, and provide feedbacks about their learning progress.

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