UBITECH participates in the kick-off meeting, in Nicosia, Cyprus (September 18, 2018) of the NAVARCHOS2 Cypriot research project, officially started on September 1st, 2018. The project is co-funded by the “Research in Enterprises” action of the multi-annual development framework of Programmes RESTART 2016-2020 for the support of Research, Technological Development and Innovation in Cyprus (Grant Agreement No. ENTERPRISES/0916/0072) and spans on the period September 2018 – August 2020. The NAVARCHOS2 project aims at the technological and innovation driven upgrade of Navarchos Fleet Management Systems so as to compete world-class related platforms that operate mainly on the cloud as a service and provide significant graphical information system capability and capacity as well as address the majority of operational and maintenance management requirements. The main features that will be designed and implemented in the frameworks of NAVARCHOS2 include: a) real-time driver-centric notification and recommendations algorithms for eco-driving behavior, b) intelligent metrics and analytics for empowering fleet managers to have a more comprehensive overview and complete control of their fleet, c) routing optimization and scheduling tools for increased fleet productivity, and d) scalable, highly available and high performance cloud-based infrastructure.
Within NAVARCHOS2, UBITECH undertakes the deployment of the Cloud-based scalable, highly available and high performance infrastructure, that safeguards the reliable operation of NAVARCHOS2 platform, benefiting from all attributes and services Cloud-based infrastructures offer including resource utilisation dynamicity, reduced failure risks, enhanced scalability and multi-tenancy. Moreover, UBITECH will develop a data collection gateway to receive data from vehicle tracking systems as well as retrieve data from open data providers (e.g. public transport data, weather data, traffic data etc.) that become available, and a complex event processing pipeline capable of addressing the main challenges associated with the traditional CEP approaches, namely: latency in the processing which has become very critical, so that CEP tasks have to be parallelized (scalability is an issue), and complexity of the situations to be detected requires networks of CEP engines in order to process the real-time data. Finally, UBITECH will work towards the development of (a) the routing optimization and scheduling engine, offering remarkable cost savings due to routing optimization, reduced carbon footprint, timely delivery service, improved management control by linking the sales process with warehousing and transportation systems, improved information flow – everyone knows the status of orders at any time, improved reporting and supports strategic logistics network design; and (b) the historical vehicle tracking system data analytics incorporating algorithms for automatic region of interest (ROI) detection, driver proficiency metric in terms of optimal routing vs driver routing, driver routing and scheduling analysis, ROI analysis (i.e. to reveal unauthorized vehicle use), driver comparing and benchmarking including fleet utilization, performance metrics (fuel usage, idling activity, harsh acceleration/de-acceleration).
