Smart Technologies for Milk Quality Control in Low-Resource Dairy Systems: A Systematic Review of IoT Sensors, Machine Learning Models, and Digital Monitoring Platforms in Sub-Saharan Africa

The review generally attempts to explore and identify the existing quality control and monitoring technologies for raw milk in Sub-Sahara Africa (SSA) region. Milk being one of the highly perishable product foods, and also highly nutritious readily available animal sourced food, requires most effective methods and technologies for its quality detection and monitoring. The technologies being looked at in this review are in form of digital systems, with a strong bias on Internet of Things (IoT) sensors and Artificial Intelligence (AI) models currently in use for milk quality control and monitoring in the region, if there are any. The review intends to provide a clear understanding of the current situation in the usage of IoT-AI systems in milk quality detection and monitoring in the region. As the general application of the IoT-AI technologies, in many different research study areas in SSA, and Africa as whole are at infant stages, the results from this review will render more room for future research explorations, as well as recommendations. This review will also help identify the gaps which exists in the implementation of IoT-AI systems on raw milk in SSA, with reference to other regions outside Africa. This will therefore enable researchers to focus more on improving the milk testing systems and processes in the bid to enhance quality milk production in the region, preventing health safety and risks associated with lack of proper and advanced systems (i.e. IoT-AI enabled systems).