Food safety is imperative to avoid food borne diseases and to ensure the public health. Monitoring of perishable food
products and early detection of degradation will avoid loss due to food wastage and ensures the freshness of food. In this
scenario, remote monitoring of fruits during transportation from field to shelf can ensure the quality of fruit. Recent
technological advancements like Internet of Things and Machine Learning (ML) has significant methodologies which can
improve the fruit quality monitory process’s cost and time efficiency. This paper describes the concepts, architecture, proof of
concept implementation and results analysis of such a Fruit Quality Monitoring System (FQMS).
