Thesis subject

IoT and edge analytics for farming equipment

In agricultural companies there is a steady increase in amount of farming equipment and machinery with the purpose of optimizing day to day business. Many of these devices are proprietary and the data is kept and analyzed on the device (think i.e. of environmental control system for barns) which is limiting, or is fully connected to Cloud which is costly and limited by volume of data and infrastructure.

But, smart devices and smart machinery that are utilizing IoT are increasingly looking into edge analytics as the most ideal solution to solve this bottleneck. Edge analytics is tightly coupled with (sitting on or close to) IoT device, so it can both collect, process and analyze right at the source.
The research can be done as general research, or in collaboration with one of Info Supports client which provides farming equipment.

Level: MSc

Research area/discipline: Internet of Things, Data analytics, Software Engineering, Farm Equipment


Short description:

This master thesis project is provided by Info Support, a software company located in the Netherlands (Veenendaal, near Wageningen) and Belgium. Info Support is a specialist in developing high-quality software solutions and a leader in the areas of artificial intelligence (AI), cloud architecture, Managed Services and IT training programs.

Interested? More information about this project and how to apply can be found here: .


    Edge analytics is a topic that is being researched within the IoT context for years. However, its application in agricultural domain is limited. The research on this topic that is happening in agricultural domain is very focused to USA market, which differs significantly from the Dutch market. In this research, your goal will be to explore applications for edge analytics within the Dutch context. Depending on your preference, you can either focus on farms or hardware provider.

    With focus on farms, your focus will be on fitting of multi-access or mobile edge computing (MEC) within the existing systems.

    If your preference lies on the side of hardware provider, you will be assessing the added value of using edge analytics for data analytics and decision support within their devices.

      Required skills/knowledge:

      Relevant literature:

      • O'Grady, M.J., Langton, D., O'Harea, G.M.P., 2019. Edge computing: A tractable model for smart agriculture? Artificial Intelligence in Agriculture, vol. 3, pp. 42-51

      For more information:

      Cor Verdouw (