利用 LoRa-WiFi 自適應雙模式山區搜救定位資料傳輸

台灣作為全球高山密度最高的島嶼之一，光是海拔 3000 公尺以上的高峰就多達二百餘座。而這些高山也吸引著世界各地的登山者前來挑戰，然而險峻的山勢同樣帶來的是山難的風險。我們希望利用先前 LoRa 的研究論文的基礎上，加上 WiFi 和 GPS 技術，建造出一套更完善的搜救系統，以期盼能逐漸取代傳統搜救方法，屆而降低搜救所需要負擔的社會成本。之所以會使用雙模 + GPS 系統，一方面是 GPS 長久以來公認有極佳的可靠性外，另一方面是藉由加上 WiFi 系統傳輸速率大的優點，彌補過往 LoRa 自身雖然傳輸距離長但是傳輸速率低的缺點。並且在未來我們也可以用這套系統傳輸透過 WiFi 模式傳輸除了文字以外的影音內容，來為待救者提供搜救需求給搜救者。並希望這套系統可以為山區搜救模式帶來新的突破。在 LoRa 和 WiFi 之間因為頻率和模組之間訊號功率上的不同，透過弗里斯傳輸方程 (Friis Transmission Equation) 推算，也估計出了理想狀態下距離上的差別，如果再加上簡單的誤差修正，我們便可以大概得知兩套系統的實際上距離。另外，在硬體設備上，我們也選擇 Raspberry Pi 作為運算的裝置，配上 Python 開源專案，包含 LoRa 模組控制、Socket 處理，以及 NMEA 0183 格式處理等，以求得整套系統上的建置、開發上因為使用高階語言而更易於修改的便利。最後，在實驗上透過遠端 SSH 終端監看搜救者與待救者在兩種模式之間的傳輸狀況：在搜尋到 LoRa 訊號後，則積極偵測 WiFi 訊號，最後進入 WiFi 模式進行較大資料量的 WiFi Socket 傳輸。透過以上的方法證明 LoRa+WiFi 雙模基本上的用於山區搜救定位資料傳輸的可行性。

關鍵字

LoRa ； Wi-Fi ；山區搜救

並列摘要

As one of the islands with the highest density of mountains in the world, Taiwan has more than 200 peaks being above three-thousand meters above sea level. These high mountains also attract many climbers from all over the world to come to challenge. However, climbing steep mountains also leads to higher risks of mountain disaster. We hope to use the foundation of previous LoRa research, with WiFi and GPS technology, to build a more comprehensive search and rescue system, in anticipation of replacing the traditional search and rescue methods, and reducing the social cost for search and rescue. The reason of using the LoRa-WiFi dual mode system alongside the GPS module is that, on one hand, GPS has long been recognized as having excellent reliability, and on the other hand, the WiFi system features the advantage of the high throughput, which makes up for the shortcomings of LoRa’s relatively low transmission rate despite the long transmission range in the past researches. And in the future, we could also potentially use this system to transmit multimedia content other than plain text through WiFi mode, in order to provide the search and rescue needs to the rescuers. It is hoped that the system may bring new breakthroughs to the mountain area search and rescue. Between LoRa and WiFi, due to the difference in frequency and signal power among modules, the ideal maximum range of these two systems are estimated with the calculation of the Friis Transmission Equation As long as a simple error correction is added, we could get a rough idea of what the actual distance between the two systems in real life. And in the selection of hardware equipment, we also choose Raspberry Pi as the computing device, coupled with the Python open-source packages, such as LoRa module control, Socket handling, NMEA 0183 format parsing et cetera, in order to obtain the convenience of easy modification with the adaption of the high-level programming language in the construction and development of the entire system. Finally, in the experiment, we use SSH terminal to monitor the transmitting status of the rescuer and the target between the two modes: after finding the LoRa signal, it will actively detect the WiFi signal, then finally switch to the WiFi mode for processing larger amount of data via WiFi Socket transmission. The above method proves the basic feasibility of LoRa-WiFi dual mode data transmission for mountain area dearch and rescue.