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Here comes Smart-En-Route project

The Smart-En-Route is a project we started on November 1st, 2021, and will last for 36 months. It is a software-as-a-service (SaaS) platform that provides intelligent logistics and business intelligence services in the area of delivery logistics.  

To simplify the complexity of the project into two main values, those would be specifically: to use smart algorithms to optimise route planning and execution, and to generate revenues while transport vehicles are on the road. The question is how to turn the vehicles themselves, which are the major cost for any transportation company, into actual revenue generators. We believe the answer is by adding small sensory devices in the cars and trucks, which converts the fleet into a dual-purpose transport vehicle. This means that the sensor collects data as the vehicle is driving, which is uploaded into a synchronized database offered to local and national authorities, environment agencies, real-estate developers, etc.; in short, any company or institution that could benefit from route optimization data and the passive real-time data sets, imagery, GPS, and video footage it simultaneously has collected.  

We have calculated that with our smart algorithms, we are cutting operational costs per vehicle down by at least 10% to an optimal 30%. Moreover, our ingenious sensors attached to the delivery vehicles as they go about attending to their tasks are collecting data related to, among other things, measurements of ozone and fine dust pollution, temperature and humidity, traffic density, noise, parking spot utilisation along urban roads, road condition reports, surveys on the thermal insulation of public households, and many other applications. 

At this halfway point of the project, we have achieved all our first strategic tasks. With the support of the Croatian Post Office, we have been able to both test and calibrate our air quality equipment, and our initial pilot tests have confirmed that the mobile data gathering concept works reliably with an overall satisfactory detection rate regardless of weather conditions. Our systems have stored images with geolocation data and stored our recorded video footage in a protected cloud network over a 4G or 5G mobile system. 

Our hope for the near future is to create a user-friendly and intuitive interface for our customers to easily access stored information, recognize key factors, and correctly interpret the information being displayed. The ultimate goal is to bring together the best aspects of machine learning and deep learning to construct a solution for our customers that optimises their investments in their core businesses while opening new opportunities for business creation.