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FOREST PATHWAYS
Joint Call 2026 - Partnering
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Partnering
Requests and Offers
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Aleksandar Savov
Bulgaria
COMICON
Small- and medium-sized enterprises (SMEs)
Early wildfire detection; Forest microclimate; Autonomous sensor networks; Edge AI; LoRa WAN; Sensor data fusion
TOPIC 1 – Climate-Resilient Forest Systems
COMICON OOD offers expertise in autonomous sensor systems for research on wildfire disturbances and climate-resilient forests. We seek a consortium under Topic 1 to investigate how local environmental conditions and early combustion signals can improve forest fire risk assessment and early warning.
Our existing wildfire sensor prototype combines measurements of volatile organic compounds (VOCs), infrared radiation, air temperature, relative humidity and atmospheric pressure with embedded AI. It uses solar energy and supercapacitor storage without batteries, LoRa WAN communication and MQTT data integration.
Potential contributions include:
Adapting sensor hardware, embedded firmware and wireless gateways to project requirements.
Supporting experimental deployments and data collection in forests with limited power and connectivity.
Jointly evaluating detection time, false alarms, energy autonomy and reliability across vegetation types and environmental conditions.
Combining in-situ observations with weather, Earth observation and ecological data to develop and test fire-risk and early-warning indicators.
Adapting our soil-moisture sensing experience to investigate drought-related conditions and their relationship with fire susceptibility.
Providing documented sensor data interfaces for integration with research and decision-support platforms.
We are particularly interested in research on the transferability of detection models between forest types, distinguishing combustion signals from environmental background, and the added value of ground measurements for wider forest monitoring.
We seek partners in forest ecology, fire science, climate and disturbance modelling, Earth observation and AI, together with forest owners or managers able to support field trials. We welcome contact from coordinators building interdisciplinary Topic 1 consortia.
Our existing wildfire sensor prototype combines measurements of volatile organic compounds (VOCs), infrared radiation, air temperature, relative humidity and atmospheric pressure with embedded AI. It uses solar energy and supercapacitor storage without batteries, LoRa WAN communication and MQTT data integration.
Potential contributions include:
Adapting sensor hardware, embedded firmware and wireless gateways to project requirements.
Supporting experimental deployments and data collection in forests with limited power and connectivity.
Jointly evaluating detection time, false alarms, energy autonomy and reliability across vegetation types and environmental conditions.
Combining in-situ observations with weather, Earth observation and ecological data to develop and test fire-risk and early-warning indicators.
Adapting our soil-moisture sensing experience to investigate drought-related conditions and their relationship with fire susceptibility.
Providing documented sensor data interfaces for integration with research and decision-support platforms.
We are particularly interested in research on the transferability of detection models between forest types, distinguishing combustion signals from environmental background, and the added value of ground measurements for wider forest monitoring.
We seek partners in forest ecology, fire science, climate and disturbance modelling, Earth observation and AI, together with forest owners or managers able to support field trials. We welcome contact from coordinators building interdisciplinary Topic 1 consortia.
COMICON OOD is a Bulgarian SME established in 1991, specialising in the development and manufacture of electronic devices, wireless communication systems and industrial automation solutions.
Our R&D capabilities cover electronic hardware, embedded firmware, low-power wireless sensor networks, communication gateways and remote monitoring. We work with technologies including LoRa/LoRaWAN, IEEE 802.15.4, Zigbee, EnOcean and industrial communication interfaces.
Relevant experience includes:
ASPires: participation in a European Commission-funded project integrating sensor networks and drone-based data collection for forest fire prevention and early detection.
4F – Flying Forest Fires Fighting: development of the sensor network and gateway within a solution for drone-assisted monitoring in remote forest areas, supported through the Horizon 2020 UFO project.
Development of a low-power wireless soil-moisture sensor and irrigation controller using Zigbee Green Power.
An EU-supported R&D project resulting in our own multifunctional wildfire sensor prototype with embedded AI.
COMICON can contribute practical expertise in translating research requirements into sensor hardware, firmware and connected monitoring systems, and in adapting prototypes for experimental evaluation.
Website: https://comicon.bg/en/
Our R&D capabilities cover electronic hardware, embedded firmware, low-power wireless sensor networks, communication gateways and remote monitoring. We work with technologies including LoRa/LoRaWAN, IEEE 802.15.4, Zigbee, EnOcean and industrial communication interfaces.
Relevant experience includes:
ASPires: participation in a European Commission-funded project integrating sensor networks and drone-based data collection for forest fire prevention and early detection.
4F – Flying Forest Fires Fighting: development of the sensor network and gateway within a solution for drone-assisted monitoring in remote forest areas, supported through the Horizon 2020 UFO project.
Development of a low-power wireless soil-moisture sensor and irrigation controller using Zigbee Green Power.
An EU-supported R&D project resulting in our own multifunctional wildfire sensor prototype with embedded AI.
COMICON can contribute practical expertise in translating research requirements into sensor hardware, firmware and connected monitoring systems, and in adapting prototypes for experimental evaluation.
Website: https://comicon.bg/en/