The Port Authority of the Bay of Algeciras (APBA) has awarded to the joint venture formed by Oritia & Boreas SL, Ayesa Advanced Technologies SA and the Polytechnic University of Madrid, the development of an Advanced System for Predicting the Operability of Vessel Infrastructures, called PROAS (Port Risk Optimized Advanced System). The award amounts to 1.7 million euros.
The aim of the project is to develop a predictive tool for the safety and efficiency of port operations based on predictions of the physical environment, planning of the scale of ships and planned operations. Precisely, the agents of the physical environment (wind, waves, currents) are directly related to the safety and efficiency of port operations. Thus, the successful bidders will develop a predictive modeling from the perspective of probabilistic techniques and artificial intelligence. To this end, they will draw on the APBA’s own sources of information, such as the Autonomous Measurement, Prediction and Alert System (SAMPA), as well as the data obtained in field campaigns for the characterization of the physical environment and the behavior of ships during their operations.
This Advanced Forecasting System will facilitate the decision making of the main agents involved in loading/unloading operations, as well as technical-nautical services and ship services. In addition to anticipate possible risk situations, PROAS is born with the purpose of optimizing the navigation of the ships that use the maritime route of the Strait of Gibraltar, and, mainly, for those that call at Algeciras, enclave that has direct connection with more than 200 ports in the world.
Finally, it should be noted that the processing of this contract is a novelty in the Spanish port system, since it is the first to be carried out through the Public Procurement of Innovation (PPI) via Competitive Dialogue. This is an administrative action that seeks to promote innovation from the public sector, through the acquisition of innovative solutions or solutions in the development phase.
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