Abstract
Long-range radio transmissions open new sensor application fields, in particular for environment monitoring. For example, the LoRa radio protocol enables connecting remote sensors at a distance as long as ten kilometers in a line-of-sight. However, the large area covered also brings several difficulties, such as the placement of sensing devices in regards to topology in geography, or the variability of communication latency. Sensing the environment also carries constraints related to the interest of sensing points in relation to a physical phenomenon. Thus, criteria for designs are evolving a lot from the existing methods, especially in complex terrains. This article describes simulation techniques based on geography analysis to compute long-range radio coverages and radio characteristics in these situations. As radio propagation is just a particular case of physical phenomena, it is shown how a unified approach also allows for characterizing the behavior of potential physical risks. The case of heavy rainfall and flooding is investigated. Geography analysis is achieved using segmentation tools to produce cellular systems which are in turn translated into code for high-performance computations. The paper provides results from practical complex terrain experiments using LoRa, which confirm the accuracy of the simulation, and scheduling characteristics for sample networks. Performance tables are produced for these simulations on current Graphics Processing Units (GPUs).
Highlights
Climate change and natural evolution seriously impact several social and economic aspects, including living conditions, human health, and development
Free space path loss (FSPL) equation was proposed for this aim (see Section 5 and Equation (9)
Two major concerns are radio waves blocked by obstacles and propagation loss in proportion with a point-to-point distance
Summary
Climate change and natural evolution seriously impact several social and economic aspects, including living conditions, human health, and development. Star organization, where a central node addresses remote sensors is the more natural technique to collect data on surfaces within a range of ten thousand square meters Complex geographic areas such as shores or islands, hills, valleys oppose physical difficulties to the radio propagation. This article describes principles of a general method based on geo-localized cellular systems It explains how a radio coverage or a physical coverage can be computed from the same framework, allowing for obtaining a better match between observation engines and observed phenomena. The approach of fine grain cellular structure and coarse grain partitioning appears to be flexible, allowing different components to coordinate. It is compatible with geographic information since each cell is localized. Appendix A will present validation results obtained by these algorithms
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
