The Innovation Fund of Montenegro has published the results of the 2024 public call for the Proof of Concept Programme. Out of all submitted applications, 19 projects were selected for funding with a total approved amount of EUR 691,103.79.
The Proof of Concept programme supports innovators in validating the technical and commercial feasibility of their ideas before moving to full product development. Funded projects span a range of sectors including information technology, renewable energy, agri-tech, medical devices and smart infrastructure.
Selected teams receive between EUR 20,000 and EUR 50,000 in grant support over a 12-month project period. In addition to financial support, beneficiaries are connected with the Innovation Fund's network of mentors and industry experts to assist with technical validation, customer discovery and preparation for the next stage of funding.
The 2024 cohort represents one of the most diverse and competitive rounds of the programme to date. Detailed project descriptions and the full list of beneficiaries are available at fondzainovacije.me.
Winners
Project name
Wildfire Early Warning System for Mediterranean Terrain
Project description
Proof-of-concept for a network of low-cost atmospheric sensors combined with satellite imagery analysis to detect wildfire ignition points up to 30 minutes earlier than existing solutions.
Project name
Skin Lesion Classification via Smartphone Camera
Project description
Validation of a convolutional neural network model capable of classifying dermoscopic images captured with an off-the-shelf smartphone attachment for preliminary screening.
Project name
Microplastic Detection Sensor for Coastal Waters
Project description
Development of a compact optical sensor prototype that can identify and quantify microplastic particles in seawater in near-real-time, enabling rapid coastal monitoring.
Project name
AI-Powered Waste Sorting Robot
Project description
Proof-of-concept for a robotic arm using computer vision to sort recyclable materials on conveyor belts, significantly increasing sorting accuracy compared to manual methods.
Project name
Drone-Based Crop Disease Mapping
Project description
Validation of an autonomous drone scouting system that uses multispectral imaging to detect early signs of crop disease and generate georeferenced treatment maps for farmers.
