AICOM scales machine learning and computer vision tools that help the Cleansing and Maintenance Division plan and prioritise urban cleansing operations. The project focuses on improving the efficiency of public service delivery by using AI to decide where and when resources are deployed in cities.
Principal Investigator: Dr Dylan Seychell
Duration: December 2024 – August 2027
Cluster: Environment
Partner/Funding: Government of Malta – Cleansing and Maintenance Division
AWIGS is a drone‑based litter detection system that uses advanced computer vision to identify different types of waste between 1 and 30 metres altitude. It aims to take technology already proven at TRL 5 into operational use at TRL 7 with the Cleansing and Maintenance Division, including smarter route planning and material‑type classification for recycling.
Principal Investigator: Dr Dylan Seychell
Duration: November 2024 – May 2026
Cluster: Environment
Funding: Xjenza Malta – Technology Development Programme Lite (TDP‑Lite) 2024
TALC combines a human‑piloted UAV, an adaptable robotic gripper and an AI decision‑making framework to pick up litter in hard‑to‑reach terrestrial environments. The project advances the integrated system from TRL 4 to TRL 6 and targets areas that are unsafe, costly or impractical to clean using ground‑based methods.
Principal Investigator: Dr Dylan Seychell
Duration: November 2025 – May 2027
Cluster: Environment
Funding: Xjenza Malta – Technology Development Programme Lite (TDP‑Lite) 2025
AAC uses AI‑guided drone flight paths to capture detailed 3D information of large‑scale objects and buildings. An initial scan is followed by custom software that identifies where more detail is needed and plots a new flight path, supporting applications in visual effects, heritage and infrastructure documentation.
Principal Investigator: Dr Dylan Seychell
Duration: May 2025 – November 2026
Cluster: Environment
Funding: Xjenza Malta – TESP Programme, in collaboration with Stargate Malta
EMBAT explores the integration of AI and computer vision for automated geospatial analysis and base map enhancement. It focuses on detecting temporal and spatial changes between aerial and satellite imagery, tackling challenges like shadow removal and object classification to support more up‑to‑date urban mapping.
Principal Investigator: Dr Dylan Seychell
Duration: February 2025 – February 2026
Cluster: Environment
Funding: MDIA Applied Research Grant (MARG) 2024, in collaboration with Malta’s Planning Authority
NBxAI investigated visual bias in Maltese news media by combining computer vision, natural language processing and media analysis. It produced tools and methodologies for understanding how visual content is used in news reporting and laid the groundwork for later media projects.
Principal Investigator: Dr Dylan Seychell
Duration: September 2023 – February 2025
Cluster: Information (Media Analysis)
Funding: Xjenza Malta – Research Excellence Programme (REP) 2023
