Implementation of A Machine Learning & Internet of Things (IoT) Model For Optimum Crop Recommendations In Zimbabwe
- Author
- Mateta, Tafadzwa
- Title
- Implementation of A Machine Learning & Internet of Things (IoT) Model For Optimum Crop Recommendations In Zimbabwe
- Abstract
- This research is based on the investigation of the efficiency implementation of a machine learning and Internet of Things (IoT) model for precision agriculture in Zimbabwe. Agriculture is one of the major contributors to the Zimbabwean economy. The problem that exists among most farmers is that they do not choose the right crop based on their soil nutrient levels, weather patterns, and agricultural region which results in major setbacks in productivity. This problem of the farmers has been addressed through precision agriculture. Precision agriculture is a farming approach that uses information technology to collect and analyse data about crops, soil, and weather conditions. A comparative study of different techniques used in crop recommendation is also included in this research. In this research, the researcher is proposing an intelligent system that uses the implementation of a machine learning and Internet of Things (IoT) model for precision agriculture in Zimbabwe. The model will use weather conditions, soil nutrient levels and soil pH data to recommend optimal crop management practices for each farmer. The model will be made available to farmers through a web application. Farmers will be able to input data about their farms, such as the soil pH, the weather conditions, and the nutrient levels. The web application will then use the model to recommend the optimal crops for the farm. The research has the potential to significantly improve the productivity of Zimbabwe's agricultural sector. The model will also help farmers to reduce their risk of crop failure.
- Date
- 2023
- Publisher
- BUSE
- Keywords
- Machine Learning
- Agriculture
- Supervisor
- N/A
- Item sets
- Department of Computer Science
