Warning System

動態超前部署 Dynamic Advance Deployment

我們團隊將最新技術與安全機制結合，打造最安全的行車記錄器系統。

在科技成長下，車廠間競爭的不再只有車輛的速度有多快，而是開發車輛中駕駛安全輔助系統。在109年度全般肇事原因首位為未保持行車安全距離與未注意車前狀態佔據六成以上的事故原因，許多車輛並未配備路況突發狀況預警系統，容易發生事故。透過影像辨識後用聲音提示駕駛並跳過車主的反應時間，系統直接給後方警示能夠在行車紀錄器及不同車輛上穩定運行。在Mio行車紀錄器上，增加使用車輛偵測系統Otsu's method 找尋影像中陰影區域來擷取陰影，並且判斷前車警示燈有無閃起，運用系統判斷後自動閃起與後鏡頭結合的警示燈，提醒後方行車。透過影像辨識判讀與執行，來達到防範疲勞或恍神以及未注意前車狀態的問題。

With the development of the improvement of technology, the competition between car manufacturers is no longer only the speed and performance of the vehicles, but also at the development of driving safety assistance systems in the vehicles. In 2020, the most common cause of accidents was the failure to maintain a safe driving distance and failure to pay attention to the state of the front of the vehicle, and both accounted for over 60% of accidents. The reason is they do not equip many vehicles with an early warning system for road conditions, so it is prone to accidents. Our system will voice prompts to the driver and skip the reaction time of the driver through the image recognition, the system directly warns to the rear that it also can run stably on the driving recorder and different vehicles.

創新構想：

在這個影像辨識技術熟成的世代下，大部分車輛未配備新的技術。在交通部所公布的數據中我們可以發現有許多的國道交通事故是因為駕駛注意力不集中、未注意前車的動態所導致的。而我們透過大數據分析以及影像模型訓練，將影像特徵辨識與我們所設計的產品做結合，為汽車的駕駛帶來更加安全且便利的行車駕駛過程。

In the new generation of AI Visual recognition technology, most people do not equip vehicles with new safety technology. In the data published in 2020 by the Department of Transportation government, we can find that many accidents on the national highway are caused by drivers who are inattentive or not paying attention to the movement of the car in front of them. Through large amounts of data analysis and AI motion model training, we combine the feature of recognition with our designed products to bring a safer and more convenient driving process.