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Eu Sustainable Network Deep Learning Stations and RoversDeep Learning embedded Stations, BorioCity v1 euRover, Eu Inspire compliant Drones autopilot, Vision Smart Tourism, Energy-Water control public GardensReduce the energy-water consumption by 20 % (average) euSustainable Deep Learning Stations and RoversCoordinator: Ayuntamiento Alhaurín de la TorreObjective: • Reduce energy and water consumption by 20 % (average) • Reduce CO2 emissions.INTRODUCTIONHardware and software system to capture data from sensors , process, analysis and dissemination of the results to public and institutions. Use of this data to analyze and take actions to reduce consumption.The system allows to actively monitor and manage electric and water usage in real time, while automatically calculating carbon footprint. This highly accurate conservation solution enables, easily displaying critical information, track performance, to manage and control resource consumption, reducing environmental impacts, and saving money.Also, other parameters, like humidity, uv, co2 etc, can be monitored.Key Features:• Real-time performance data display.• Up to 500 embedded units connected.• Bidirectional communications with the units.• Remotely updatable.• Highly accurate, robust data acquisition model.• 2-way integration with leading control systems.• User-configurable alerts and alarms.• Automatic alerting via email, text or SMS.• Trend analysis and historical comparatives.• Tracks renewable energy and water technologiesAIMSRover and smart stationsDeep learning real useRover use for education at schools (shows)ENERGY MONITOR PLUS MERGEDS AND ANALYSIS OTHER DATA FROM ENVIRONMENT SENSORS.All units are connected with energy consume thought remote wifi with non-invasive current sensors. The energy consume data are merged with all the other sensors temp, humidity, barometric, uv

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