The project aims at developing and piloting three main services: Vegetation Management, Infrastructure Risk Detection and Disaster Management. All electric network owners need to make sure that vegetation is managed on the network right-of-way. The automatic Vegetation Management Service improves Vegetation management efficiency and quality. New roads, building sites, and unauthorised structures (buildings, constructions, wood heaps) near or under electricity networks may cause hazards and potential risks to the network.

SatADAPT is a Predictive Maintenance (PDMA) system that uses distributed Artificial Intelligence (AI) to predict potential failures of industrial equipment. Its versatility allows the use in several industries, such as wind power, manufacturing and oil and gas. The value that SatADAPT brings to users consists in the increased uptime of the machinery, due to the reduction of the number of failures and the avoidance of unplanned down time due to unexpected equipment failure.

SARSentry provides an automated near real time (NRT) forest monitoring system producing forest change maps applicable across landscapes, informing on both forest loss and forest degradation. The service focuses on the Brazilian state of Para tackling illegal logging intensity in the Amazon but is offered to all national and sub-national governments and companies that want to assess, monitor and report forest use, degradation and conversion.

The objective is to design, implement, test and validate a dedicated Alert System (AS) for the monitoring of the public green, in particular those located inside areas of relevant historical and cultural sites. The proposed service monitors the health of vegetation by indirect estimation of bio-physical parameters using Sentinel-2; Landsat-8 and PRISMA satellite images, fused with high resolution satellite and/or UAV images. Additionally, the service monitors in real-time trees stability leveraging on a network of in situ sensors.

The goal of the Ranglo project is to deliver a data integration and predictive analytics service for rail freight in the UK based on near real-time tracking of railcars. The software platform connects to existing internal & external data sources to allow for data exchange and integration between the different rail freight stakeholders. The tracking is performed by a Satellite-IoT and multi-constellation GNSS device that is installed directly into railcars and can be connected to multiple sensors depending on the role of the railcar.

The Lunar project is aimed at realising a dynamic door-to-door commute service able to provide better access to hospitals for employees who are often working shifts at odd times of the day when public transport is limited/unavailable. The managed commute service can contribute to significantly reduce the pressure on car parking facilities of the hospital. Satellite Navigation technologies are used to achieve an understanding of the current location of vehicles and optimise the service because of accurate, real-time location information and routing data.

The activity aims at implementing a cultural heritage monitoring and management system in support of ordinary and extraordinary management activities. The service allows monitoring of soil and buildings stability and deformations, anthropic activities (identification of waste and debriefs), weed
vegetation and the concentration of pollution sprays in the urban environment. The system is based on the integration of different technologies: satellite, RPAS, in situ IOT monitoring, image recognition and advanced modelling. The

Ogor Yield is a yield forecasting service for the major crops in Romania. It allows farmers to anticipate the volume of crop to be harvested and plan the work in advance and with higher quality: harvesting effort, storage required, logistics, price estimation. This translates ultimately into higher margins and better practices for the farmers. The service uses multiples data streams including Sentinel-2 data and is the newest addition to the Ogor Agrictech service portfolio.

This project aims at demonstrating a proactive monitoring and
assessment of oil slicks service for offshore oil activities. The
proposed solution exploits Earth Observation and Navigation
space assets to provide offshore Oil & Gas operators with a
system to enhance their situational awareness by detecting the
presence of pollution slicks and correlate their position and timings to rigs, vessels or other infrastructure. The expected
benefits for Oil & Gas companies are savings due to more

NHSpace is aimed at developing an online application allowing
to analyse a range of geospatial data targeting health
inequalities by combining a variety of ground and space
datasets with advanced analytics. This allows users to gain
insights on population demographics and better understand
correlations to the risk factors causing health inequalities at a
community level. The outcome allows more informed decisions
on the allocation of resources and time to those who need it
most and assist in policy and strategy decision making to