Innovative IoT Sensor Based Rangeland Monitoring in Northern Kenya’s ASALs
The topic is open and also suitable for GEM students in track 3 – GEM for Ecosystems & Natural Resources.
The arid and semi-arid lands (ASALs) of northern Kenya face pressing challenges due to climate change, environmental degradation, and socio-economic vulnerabilities. Accurate and timely monitoring of rangeland conditions is vital for supporting pastoralist communities and ensuring sustainable livestock management. Traditional methods of data collection are often labour-intense, expensive, and spatially limited, while satellite-based monitoring, though valuable, can lack the ground-truth needed for local decision-making.
This MSc topic explores the use of Internet of Things (IoT) sensors as a transformative solution for rangeland monitoring. By leveraging and expanding existing LoRaWAN networks, the MSc research aims to develop innovative sensor-based approaches to track environmental or livestock variables. These could include:
- Monitoring vegetation status, phenology, and fodder availability through environmental sensors.
- Tracking rainfall patterns or microclimatic variations with meteorological sensors.
- Using movement sensors on livestock to understand grazing behaviours.
The sensor data will complement and enhance satellite-based assessments, offering high-resolution insights critical for rangeland resilience. Creative sensor placements, such as hidden or tamper-resistant designs to prevent theft, and adaptable deployments on animals, vegetation, or the landscape, will be key aspects of this work. You are encouraged to be creative.
You will work towards the following objectives:
- Conceptualization and Design:
Conduct a review of existing IoT applications in rangeland and livestock monitoring and design an innovative IoT-based monitoring system using off-the-shelf or custom-designed sensors.
- Implementation and Deployment:
Install and configure IoT sensors in strategic locations (e.g., on animals, vegetation, or fixed points in the landscape).
- Data Collection and Analysis:
Collect and process data on environmental or livestock parameters and integrate IoT data with satellite imagery or other remote sensing data.
- Evaluation:
Assess the IoT system’s effectiveness, reliability, and potential for scaling and explore the value of IoT insights for improving pastoralist resilience and sustainable rangeland management.
This MSc project is embedded in the RANGE (Resilient Approaches in Natural ranGeland Ecosystems) Project, which supports resilience in rangeland ecosystems. It will involve close collaboration with local communities and stakeholders in northern Kenya, ensuring that the outcomes align with the needs of ASAL communities and the broader goals of The RANGE project.
Key Skills and Opportunities
This MSc topic is ideal for students interested in the exciting and growing field of IoT technology, environmental monitoring, and applied research for sustainable development. You will have the opportunity to design and implement a simple IoT monitoring system, while contributing to real-world challenges in one of the most climate-vulnerable regions of the world.
Shelemia Nyamuryekung'e, Transforming ranching: Precision livestock management in the Internet of Things era, Rangelands, Volume 46, Issue 1, 2024, Pages 13-22, ISSN 0190-0528, https://doi.org/10.1016/j.rala.2023.10.002.
Cukjati, Jernej & Mongus, Domen & Zalik, Krista & Zalik, Borut. (2022). IoT and Satellite Sensor Data Integration for Assessment of Environmental Variables: A Case Study on NO2. Sensors. http://dx.doi.org/10.3390/s22155660
This project integrates cutting-edge technology (IoT sensors) with spatial data analysis, addressing the challenges of data scarcity in remote ASAL regions. It combines data collection, geospatial data integration, and environmental monitoring, aligning with Spatial Engineering’s emphasis on innovative, interdisciplinary solutions for real-world problems.