The UNODC Illicit Crop Monitoring Programme (ICMP) uses GIS and geospatial analysis, satellite imagery and field surveys to monitor the extent and evolution of illicit crop cultivation and production. The project seeks to research and eventually apply (semi-) automated methods such as deep learning and big data analysis for improving area estimates for illicit crop cultivation. Moreover, research is conducted on spectral based yield information, and the early detection of illegal landing runways applying AI techniques.
Activity Type Research/Reports/AssessmentsAI Tools/SolutionsThe pilot project seeks to improve the data and knowledge related to incidents of illegal fishing across the world. The objective was to use innovative techniques to identify and collect new data. Generative AI’s deep research capabilities were used to identify and expand the range of relevant data sources. AI-assisted tools were used to verify and adapt to the varying structures of web pages, ensuring the web scraping process remains robust despite differences in page layouts and metadata formats across sites.
Activity Type Research/Reports/AssessmentsThe partnership (EO4SECURITY) focuses on developing services for UNODC to investigate environmental crimes and illicit trafficking utilizing Earth Observation and Open-Source Intelligence (OSINT) data and AI processing techniques. OSINT and Large Language Models (LLMs) are leveraged to “web scrape” traditional and social media to retrieve information about the convergence of criminal activities in specific areas. After a successful conclusion of the first phase with applications in the Mekong region (illegal drug trafficking and scam cities) and Brazil (illegal deforestation and gold mining). The project was extended until 2026 focusing on Peru.
Activity Type Research/Reports/AssessmentsTechnical assistanceTrainings/workshopsThe pilot project seeks to improve the data and knowledge related to incidents of illegal fishing across the world. The objective was to use innovative techniques to identify and collect new data. Generative AI’s deep research capabilities were used to identify and expand the range of relevant data sources. AI-assisted tools were used to verify and adapt to the varying structures of web pages, ensuring the web scraping process remains robust despite differences in page layouts and metadata formats across sites.
Activity Type Research/Reports/Assessments