RE-MOV

The Project aims to develop a sustainable management model for the distribution of temperature-sensitive products to ensure the maintenance of the optimal temperature for each product during transport so to guarantee:

- quality, hygiene, and safety of the product
- energy saving and cost reduction                        
- maximum customer satisfaction and chain efficiency

Re-mov proposes a management model based on automated, timely and constant collection of information, centralized data management and predictive analysis of machine learning systems. This model is more innovative than the current one based on data collection that is often manual, random and uncoordinated, so it is considered faster and safer to keep all products at the minimum required temperature (that of meat in the case of food) regardless of the type of product, with unnecessary waste of energy. 

It is an integrated system that includes:

• a real time onboard system that performs detection and acquisition of information related to cold storage, vehicles, routes, and all relative temperatures (including external temperatures)
• an App for drivers that allows them to enter information on shifts, stops, routes, deliveries
• an App for users that allows them to book and track the transportation and delivery service and to evaluate the quality of the product delivered
• a central machine learning system and a power BI dashboard that process self-learning information in a progressive manner and suggest routes and deliveries based on the necessary stops and impacts on the cold chain and maintaining optimal temperatures.