Bike Tracking System With Dead Man Alert > 자유게시판

Security for iTagPro smart tracker bike riders is a must, with street bike or mountain bike accidents occurs and as quickly as attainable, emergency personnel should find you. That is even more vital when you journey alone. As bike user, I understand how important is safety for bikers and I would like to construct a simple, low power and excessive coverage device to monitor the rides and have a safety system in case of an accident. Thanks to the big coverage of sigfox community in Spain and iTagPro tracker an Arduino MKRFOX1200 with an IMU and a GPS module, it's attainable to monitor the biker and in case the bike falls and it's on the bottom for more than a configured time, ItagPro the devide sends and alarm with the GPS coordinates. This system checks each a configured timer (for instance 10 seconds) the bike the inclination within the three axis (X, 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 need to be warned in case os accident. Also, this system sends the GPS position or IMU data every a configured timer, for instance 10 minutes. In the final version, the gadget is positioned in the bottom of the bike bottle holder. This demo video exhibits that about 15 seconds lapse because the system detects the bottle fall until a SMS is obtained to the configured cellphone number. Also, this machine could possibly be used for tracking your bike rides or be tracked by your family or mates, or iTagPro locator in case your bike is stolen, the bike can be positioned in a short while. As an anti-theft system could possibly be hidden contained in the bike body sooner or later. Another application for ItagPro this system could possibly be for members tracking in bike competitions with both features safety and dwell monitoring for organizers. Additionally, with a low power bluetooth, this system might be controlled by a smartphone and add extra features. For example ship your location to your bike group to know the way far you're kind them.

Object detection is extensively used in robotic navigation, intelligent video surveillance, industrial inspection, aerospace and plenty of different fields. It is a vital department of image processing and laptop vision disciplines, and can also be the core part of intelligent surveillance techniques. At the identical time, target detection can also be a primary algorithm in the sector of pan-identification, which plays an important position in subsequent duties akin to face recognition, iTagPro locator gait recognition, crowd counting, and occasion segmentation. After the primary detection module performs target 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 method It also consists of: displaying the above N detection targets on a screen. The first coordinate information corresponding to the i-th detection target; acquiring the above-mentioned video body; positioning within the above-mentioned video body according to the primary coordinate data corresponding to the above-talked about i-th detection target, acquiring a partial picture of the above-talked about video body, and iTagPro locator determining the above-mentioned partial image is the i-th image above.

The expanded first coordinate info corresponding to the i-th detection target; the above-mentioned first coordinate information corresponding to the i-th detection target is used for positioning in the above-mentioned video frame, including: according to the expanded first coordinate info corresponding to the i-th detection goal The coordinate data locates in the above video frame. Performing object detection processing, if the i-th image includes the i-th detection object, buying position data of the i-th detection object in the i-th image to acquire the second coordinate information. The second detection module performs target detection processing on the jth picture to find out the second coordinate information of the jth detected goal, where j is a constructive integer not higher than N and not equal to i. Target detection processing, obtaining multiple faces within the above video body, and first coordinate info of every face; randomly obtaining target faces from the above multiple faces, iTagPro locator and intercepting partial pictures of the above video body in response to the above first coordinate data ; performing goal detection processing on the partial picture by means of the second detection module to obtain second coordinate information of the target face; displaying the goal face in keeping with the second coordinate data.