Bike Tracking System With Dead Man Alert

Security for bike riders is a must, with highway bike or mountain bike accidents occurs and as soon as doable, emergency personnel must locate you. This is even more vital whenever you journey alone. As bike consumer, I know the way necessary is security for bikers and I need to construct a easy, low energy and high protection device to watch the rides and have a safety system in case of an accident. Thanks to the big coverage of sigfox community in Spain and an Arduino MKRFOX1200 with an IMU and a GPS module, it is potential to watch the biker and in case the bike falls and it is on the bottom for more than a configured time, the devide sends and alarm with the GPS coordinates. This machine checks each a configured timer (for instance 10 seconds) the bike the inclination in the three axis (X, iTagPro Y and Z) with the IMU.



This database is checked by an Arduino Leonardo ETH with an Arduino GSM Shield 2 and sends SMS to someone cellphone you wish to be warned in case os accident. Also, this gadget sends the GPS place or IMU information each a configured timer, for instance 10 minutes. In the ultimate version, the gadget is placed in the base of the bike bottle holder. This demo video reveals that about 15 seconds lapse for the reason that system detects the bottle fall till a SMS is received to the configured phone number. Also, this system could possibly be used for tracking your bike rides or be tracked by your family or buddies, or in case your bike is stolen, the bike can be positioned in a short time. As an anti-theft gadget may very well be hidden inside the bike frame in the future. Another application for this machine may very well be for members monitoring in bike competitions with both features safety and dwell tracking for organizers. Additionally, with a low energy bluetooth, this gadget might be controlled by a smartphone and add more options. For example ship your location to your bike group to know how far you are kind them.



Object detection is widely utilized in robotic navigation, clever video surveillance, industrial inspection, aerospace and many other fields. It is an important branch of image processing and computer vision disciplines, and can be the core part of intelligent surveillance techniques. At the identical time, target detection can also be a basic algorithm in the sphere of pan-identification, which performs a vital function in subsequent duties resembling face recognition, gait recognition, crowd counting, and instance segmentation. After the primary detection module performs goal detection processing on the video body to acquire the N detection targets in the video body and the first coordinate information of every detection goal, the above methodology It additionally consists of: displaying the above N detection targets on a display. The primary coordinate info corresponding to the i-th detection goal; obtaining the above-mentioned video frame; positioning within the above-mentioned video frame according to the primary coordinate information corresponding to the above-talked about i-th detection goal, acquiring a partial picture of the above-mentioned video body, and figuring out the above-talked about partial picture is the i-th picture above.



The expanded first coordinate info corresponding to the i-th detection goal; the above-mentioned first coordinate info corresponding to the i-th detection goal is used for positioning in the above-talked about video frame, together with: iTagPro reviews in accordance with the expanded first coordinate info corresponding to the i-th detection goal The coordinate information locates within the above video body. Performing object detection processing, if the i-th image includes the i-th detection object, buying position information of the i-th detection object within the i-th image to acquire the second coordinate information. The second detection module performs target detection processing on the jth image to find out the second coordinate information of the jth detected target, where j is a optimistic integer not better than N and not equal to i. Target detection processing, acquiring multiple faces within the above video body, iTagPro locator and first coordinate information of every face; randomly acquiring target faces from the above multiple faces, and iTagPro reviews intercepting partial photos of the above video body according to the above first coordinate information ; performing goal detection processing on the partial picture through the second detection module to acquire second coordinate information of the goal face; displaying the goal face in accordance with the second coordinate info.