The three-tier community alert system enables rapid reporting of HEC through established communication channels. Farmers immediately contact VGS via dedicated phones when elephants approach farmlands, while village chairs serve as secondary contacts to verify and escalate critical incidents. This decentralized structure ensures 24/7 coverage across member villages, with response prioritization based on crop vulnerability and elephant herd size. The system incorporates community feedback loops, where farmers receive call for confirmations of Response Unit coming and after incident resolution farmers discuss the incident with the Unit, building trust in conservation efforts.

STEP and Honeyguide Foundation facilitated training at MBOMIPA WMA to equip 12 VGS (40% women) + 2 drivers with effective techniques for safeguarding community farms from elephant damage. The training equipped Scouts with knowledge on elephant behavior and how to use the HEC toolkit (torches, horns, chili crackers, and roman candles) to push elephants away from farms. Participants also learned techniques for safely relocating elephants based on their behavior and group composition (namely, whether they were all-male, all-female, or mixed groups). Refresher trainings have been regularly provided to the team to ensure safety.

The debriefing occurs both during and after the game. Brief debriefs can take place after each session to gauge participants’ feelings about the game at individual and territorial levels. These are kept light to maintain the game’s flow.

Once the game is over, a more in-depth debriefing can take place. It doesn’t necessarily have to happen immediately after the game; it could be scheduled for the following day. Some preparation is required for this discussion. The facilitator should bring a list of prepared questions and a printed map of the territory. During this debriefing, participants will identify the challenges they faced regarding land use, as well as the causes of those challenges. Key actors needed for resolution and potential solution ideas will also be discussed. The map serves as a visual aid to guide the discussion. Some basic questions that could be asked include:

• What happened during the game? How much, how quickly, and why did the soil degrade?
• What were the main conflicts that arose during the game? Between which actors?
• Did you find any solutions?
• Did you try to implement them? What was the outcome?

Of course, the questions can be more specific and adapted to the participants and the situations that arose during the game. 

To start the game, a map representing the local area is first created. The facilitator begins by asking participants to describe their land and sketches features as they respond. Once all key elements are outlined, color-coded hexagonal tiles, called ‘parcels,’ are placed over the drawing to form the board. Each tile’s color reflects soil fertility, ranging from high to low fertility. These parcels generate trees and resources based on their fertility levels. The board is designed to represent various landscapes, including mature forests, young forests, savannahs, and rivers or lakes. Wildlife such as forest animals and fish can also be added. Additionally, extra tiles may be introduced to capture local specifics.

Next, players are assigned a certain number of family members to manage. For each family member, they choose activities such as farming, breeding, or fishing to gather resources. To encourage new perspectives, the facilitator invites players to select activities different from those they do in real life. The game proceeds in rounds alternating between rainy and dry seasons, with each season affecting activities and resource availability. Throughout the game, the facilitator introduces events and, at the end of each season, leads a brief debrief to discuss players’ feelings about the current situation.

Before the game can be played, the facilitator must be trained, and the participants selected.

The choice of a game facilitator should fall on someone knowledgeable about land use issues and who knows the social background, culture, language and customs of the local communities, as this expertise is crucial for leading the final debate. To prepare the facilitator, a good approach is to have them play the game once, along with other future facilitators. The goal of this first trial is not only to train them, but also to adjust the game rules to the local context. The game functions better when tailored to the local context. After the trial, a debriefing should be conducted to assess what worked well, what didn’t, and to determine what events or tokens could be created to best represent the region where the game will be played.

To select the participants, the organizers can work with the village chiefs, who will help identify and mobilize the various groups affected by the land use issue to participate in the game. They also can assist in selecting an appropriate location for the game to take place.

Participants should come from diverse groups, including young people, women, farmers, breeders, and others. During the game, it may be beneficial to sometimes keep these groups together and at other times mix them, in order to foster different dynamics and debates.

Connecting the public: This mini program aims to promote the mainstream of biodiversity conservation by desensitizing current monitoring data in the industry and designing low threshold interactions for the traditional data labeling process. This allows the public to participate in the training process of biodiversity models in a more accessible and intuitive way through the mini program. On the one hand, the public can enjoy and learn about the most authentic protection monitoring images through the form of "playing games"; On the other hand, the power of the public can be utilized to continuously train a universal model of biodiversity, achieving the goal of citizen science in the process.
Through product design, 'Wild Friends' breaks down the process of annotating and verifying institutional data into tool based tasks, reducing the initial training costs of institutions. With simple guidance, volunteers or the general public can complete basic annotation content.
The first step is to check for the presence of animals (manually identified or judged by AI);
Step two, estimate the number of animals (manually determined);
Step three, select animals (manually or through AI evaluation of selection accuracy);
Step four, identify the name of the animal (manually selected or judged by AI);
Step five, randomly allocate cross validation in the background. Ensure the accuracy and consistency of data.
 

AI species recognition: This product uses AI recognition as the underlying technology, with endangered species as the core recognition object. It trains a large biodiversity recognition model that can support monitoring of mountains, rivers, forests, fields, lakes, grasses, and sands systems. The model is free and open to public welfare organizations dedicated to biodiversity conservation, such as research institutes, conservation organizations, and individuals. The reason why "wild friends" are so powerful is because they have a powerful "engine": YOLO World.
As the underlying universal model of 'wild friends', its primary characteristic is strong learning ability. It has powerful multimodal zero sample recognition and few sample recognition capabilities, which means it can quickly identify animal location regions and species information of multiple species through a small number of samples. For example, to recognize a new species, traditional models require thousands of photos and several days of training; YOLO World only requires a small number of photos and training iterations to achieve rapid adaptation.
Secondly, it has a high degree of tolerance. No longer limited to training and prediction of specific species, it has strong open vocabulary recognition ability and zero sample recognition ability, and can accurately identify and locate untrained species. For example, traditional models can only recognize trained species such as tigers and antelopes; The new model can also recognize snow leopards and foxes simultaneously - even if it has never trained these two animals before.
Another advantage of "wild friends" is that they spend less money. Common AI models heavily rely on high-performance acceleration cards, which result in high costs for both hardware environment and maintenance operations.