We have developed and released Mindgrate, a mobile app which allows legal migrants, refugees and asylum seekers to better integrate themselves to the Cyprus society, assisting them to locate a job. Mindgrate addresses numerous barriers which hindered migrants during their integration to the country in the past.
We have published open-source code for agtech, allowing farmers and developers to use various popular path planning algorithms to find the best solution for a swarm of agents (drones and/or ground robots) to cover an agricultural field for a range of operations (e.g. pruning, spraying, monitoring, crop collection, etc.).
We have created a computer vision model, based on Deep Siamese Neural Networks, for detecting land use change from satellite imagery, using a weakly supervised learning technique, for accelerating the training process without significant effort in data annotation/labelling.
We have identified, listed and visualized 63 important key performance indicators used by 193 countries around the world to measure climate change. To define goals for cities and countries in regards to mitigating climatic change, we first need to understand which the important KPIs are, how they can be measured and which values they take. Then, each country can calculate its performance based on these KPIs, setting realistic goals for better performance in the near future.
We have trained a computer vision model to take advantage of the shadow map of a remotely sensed monocular image to calculate its heightmap with high precision, creating digital surface models without the need of expensive equipment and large costs.
CovTracer-EN, which constitutes the official national mobile phone application for COVID-19 contact tracing in Cyprus based on the GAEN API, developed by our group in a joint effort with other MRG groups at CYENS, has been recently launched around the country, counting 25,000 users after one month from official release.
We have published open-source code for fire authorities around the world, including mobile apps for citizens and web apps for admin personnel, which can be used to model the propagation of wildfires in real-time, assisting users to safely evacuate the area using our mobile apps.
We have examined whether animal manure constitutes an effective strategy to increase soil organic carbon stocks in the Mediterranean as a mitigation climate change action.
We have proposed an effective solution to the contamination of soils and water due to animal manure, by suggesting to transfer this manure from livestock farms to crop fields, to be used as fertilizer. We used Catalonia, Spain as a case study, employing a nature-inspired algorithm based on ants' foraging behaviour to solve the manure distribution problem.
We have developed a contact tracing app to fight the COVID-19 pandemic, which became the official app used by the Government of Cyprus.
We have considered various algorithms to investigate how swarms of ground robots and/or unmanned aerial vehicles (drones) could collaborate together for solving various tasks in agricultural fields efficiently.
We have predicted parking occupancy in short-term (i.e. next 60 minutes) and in real-time at the central parking station of Arnhem, the Netherlands. Our results have beaten the state-of-art predictions for parking occupancy.
We have proposed the use of synthetic data for training deep learning models, in cases where real-world datasets are inexistent or difficult to prepare/create. We have applied this concept in aerial photography for identifying disasters (i.e. fire, smoke, collapsed buildings) and to count houses and buildings.