In Shennongjia National Park, central China, a site included in the IUCN Green List of Protected and Conserved Areas, the recovery of the rare Asiatic black bear (Ursus thibetanus) is a conservation success worth celebrating. However, as black bear populations recover, their habitats increasingly overlap with areas used by local communities. For beekeepers, this can result in damaged apiaries and an increased risk of human–bear encounters.

This is the type of real-world conservation challenge that the Tech4Nature initiative aims to address, by equipping protected areas with intelligent solutions to support fair and effective management. In April 2026, the Tech4Nature China team reached a major milestone: AI-powered automatic recognition cameras and pulsed electronic fences were installed across five pilot sites in Shennongjia. This marks an important step towards reducing human–bear conflict through digital innovation.

Understanding human-bear interactions in Shennonjia

The project builds on a Shennogjia National Park.

A network of 93 camera traps recorded 497 valid detections of black bears. Results indicate that peak activity occurs between July and November, with seasonal vertical migration across elevations driven by food availability.

To complement ecological monitoring, community surveys were conducted in August 2025 at two sites with high incidences of human–bear conflict in Shennongjia. At the Qianjiaping Seedling Experimental Base, managed by Shennongjia National Park, villagers reported that black bears frequently breach northeastern fences to raid beehives. Existing deterrents such as red warning flags have proven ineffective. These findings highlight the limitations of conventional monitoring approaches in addressing the practical challenges of human–bear conflict, often resulting in delayed responses and reduced effectiveness.

© ENCI-CAF

Tech4Nature in Shennonjia is designed to address this gap by integrating field hardware, connectivity, intelligent detection and rapid alerts into a single system. The project combines AI-powered cameras, electronic fencing and a real-time warning system to support an integrated approach to human–bear conflict prevention. This approach aims to protect wildlife while safeguarding community safety and livelihoods and to provide a scalable, China-based model for global human–wildlife conflict management.

The April 2026 milestone: Installation completed across five pilot sites

From April 15 to 20, 2026, the project team from the ENCI-CAF, with support from local beekeepers and staff of the Shennongjia National Park Research Institute, deployed and installed 4G-enabled AI infrared cameras with automatic recognition, along with pulsed electronic fences, at five selected pilot sites in Shennongjia National Park, Hubei Province.

© IUCN, Tech4Nature China

© IUCN, Tech4Nature China

© IUCN, Tech4Nature China

The following equipment was deployed across the five pilot sites:

• Five 4G-enabled AI infrared cameras with automatic recognition (for real-time detection and identification)
• Ten standard infrared cameras (to expand monitoring coverage)
• Pulsed electronic fences at four sites with concentrated beehives

With these installations, the foundational field infrastructure for the Tech4Nature flagship project is now in place.

Turning detection into prevention: Real-time alerts for rapid response

The system is configured to automatically transmit detection data, including time, location and real-time images, to a dedicated early warning mobile application. When a black bear is identified, an alert is immediately sent to designated users.

To date, three local beekeepers have installed the application; all three are also staff members of the Shennongjia National Park Research Institute. In addition, members of the ENCI-CAF project team are connected to the system, enabling timely receipt of alerts and coordinated response.

Early proof within hours of deployment

Shortly after installation, one of the 4G-enabled AI infrared cameras detected a sika deer (Cervus nippon) and transmitted real-time data and imagery to the mobile application. This initial result demonstrates that the system is functioning as intended.

© ENCI-CAF

Next steps: Testing under real conditions

With installation now complete, the next phase of the pilot will focus on operational testing under real-world conditions. As Asiatic black bears emerge from hibernation and become more active during the summer months, the project team will validate system performance using actual bear detections. This will confirm whether alerts are delivered accurately and in a timely manner to both beekeepers and park staff.