Lost in the woods: Forest vegetation, and not topography, most affects the connectivity of mesh radio networks for public safety

Abstract

Real-time data- and location-sharing using mesh networking radios paired with smartphones may improve situational awareness and safety in remote environments lacking communications infrastructure. Despite being increasingly used for wildland fire and public safety applications, there has been little formal evaluation of the network connectivity of these devices. The objectives of this study were to 1) characterize the connectivity of mesh networks in variable forest and topographic conditions; 2) evaluate the abilities of lidar and satellite remote sensing data to predict connectivity; and 3) assess the relative importance of the predictive metrics. A large field experiment was conducted to test the connectivity of a network of one mobile and five stationary goTenna Pro mesh radios on 24 Public Land Survey System sections approximately 260 ha in area in northern Idaho. Dirichlet regression was used to predict connectivity using 1) both lidar- and satellite-derived metrics (LIDSAT); 2) lidar-derived metrics only (LID); and 3) satellite-derived metrics only (SAT). On average the full network was connected only 32.6% of the time (range: 0% to 90.5%) and the mobile goTenna was disconnected from all other devices 18.2% of the time (range: 0% to 44.5%). RMSE for the six connectivity levels ranged from 0.101 to 0.314 for the LIDSAT model, from 0.103 to 0.310 for the LID model, and from 0.121 to 0.313 for the SAT model. Vegetation-related metrics affected connectivity more than topography. Developed models may be used to predict the connectivity of real-time mesh networks over large spatial extents using remote sensing data in order to forecast how well similar networks are expected to perform for wildland firefighting, forestry, and public safety applications. However, safety professionals should be aware of the impacts of vegetation on connectivity.

Recent Applications of Smart Technologies for Monitoring the Sustainability of Forest Operations

“…LS systems can be based on GNSS-RF paired with smartphones, and these systems are often used in the USA [107]. However, it is important to highlight that, as with every precision forestry application, this system is a support tool but not a panacea for all problems.…”

“…However, it is important to highlight that, as with every precision forestry application, this system is a support tool but not a panacea for all problems. Indeed, we have to continuously be aware that GNSS in the forest environment can experience occlusion problems; for instance, in the study by Zimbelman and Keefe [107], on average the full GNSS-RF network was connected only 32.6% of the time (range: 0% to 90.5%), and the mobile radios were disconnected from all other devices 18.2% of the time (range: 0% to 44.5%). Therefore, such systems can help to monitor working operations, but every forest operator, even if equipped with this system, should continue to maintain a high level of attention while performing his/her tasks while also monitoring the situations of his/her co-workers to prevent possible accidents and act quickly in the case of injuries.…”