Operation of LisaAlert sans mobile internet: Can horses or drones take over?
In the Siberian city of Tomsk, a unique collaboration between technology and tradition is being employed in the search for missing persons. The Tomsk "LizaAlert" team, a local search and rescue organisation, is utilising a quadcopter (UAV) for aerial searches, while horse teams provide essential ground mobility in the dense forests and wilderness typical of the region.
The "LizaAlert" team's quadcopter takes around 1000 photos during each search, which are uploaded to a network for review. However, due to ongoing mobile internet disruptions in the Tomsk region since August 1, as reported, these images are not always accessible, causing communication and coordination issues among the search teams.
This technological limitation has affected various aspects of life in Tomsk, including sending messages, taxi services, and bank card payments. Despite these challenges, the Tomsk division's press service has managed to adapt, using Wi-Fi when available to cover for each other when one representative is offline for a prolonged period. No other divisions have reported similar difficulties.
Horses, trained by the Tomsk "LizaAlert" search team, have proven to be valuable assets in expanding the search area during "sweeps." Their height increases the distance between searchers, allowing them to cover more ground effectively. However, the lack of horse trailers in Tomsk presents a challenge, with many horse owners releasing their horses for search and rescue near their equestrian sports club.
Not all new volunteers have the necessary navigation skills, which is another hurdle in the search efforts. The worst-affected by the mobile internet disruptions are the information coordinators, who face difficulties with file transfers, especially without Wi-Fi.
In regions such as Tula, Lipetsk, Oryol, Leningrad, and the Altai Krai, rescuers have experienced GPS disruptions, forcing them to revert to traditional compasses and paper maps. This combined approach, where neural networks assist in analysing large datasets, images, or sensor inputs to detect patterns or anomalies, and horse teams provide physical terrain coverage, is proving to be an effective strategy in challenging search scenarios.
While details about the use of neural networks in Tomsk specifically are scarce, their potential in aiding search operations by analysing aerial or satellite images and optimising search patterns based on data inputs is undeniable. A notable example from Wyoming demonstrates this synergy, where drones with cameras and FLIR capabilities, multiple dog tracking teams, and horse and foot teams were employed in a search, with data from aerial assets likely processed by advanced algorithms or neural networks to identify points of interest.
In conclusion, neural networks aid by processing and analysing sensor data and imagery to prioritise search areas. Horse teams provide essential ground mobility in challenging terrains such as forests and wilderness, including regions like Tomsk. Mobile internet disruptions hamper communication and coordination, limiting timely data sharing and the effectiveness of technology-reliant search tools. This combination of modern AI techniques with traditional on-the-ground mobility is crucial to improve missing persons searches in remote or rugged areas, yet depends heavily on reliable connectivity for full effectiveness.
- The "LizaAlert" team's quest for technological advancement doesn't stop at the quadcopter; they are considering the integration of neural networks to analyze aerial or satellite images and optimize search patterns in future operations, similar to the success demonstrated in Wyoming.
- Amidst the challenges posed by mobile internet disruptions, education and self-development platforms have become increasingly useful for the Tomsk division, providing resources for learning navigation skills, general news, and sports updates, serving as valuable tools to bridge the gap during communication lapses.
