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The electromagnetic parking sensor (EPS) was re-invented and patented in 1992 by Mauro Del Signore. [2] Electromagnetic sensors rely on the vehicle moving slowly and smoothly towards the object to be avoided. Once an obstacle is detected, the sensor continues to signal the presence of the obstacle even if the vehicle momentarily stops.
An induction or inductive loop is an electromagnetic communication or detection system which uses a moving magnet or an alternating current to induce an electric current in a nearby wire. Induction loops are used for transmission and reception of communication signals, or for detection of metal objects in metal detectors or vehicle presence ...
OBDuino is an open source trip computer design based on the Arduino platform. An OBDuino may be assembled and customised by an electronics hobbyist; it displays information such as instantaneous fuel economy (e.g. miles per gallon, L/100 km or kilometres per litre), engine tuning parameters etc. on an LCD.
The Crumbuino-Mega is a low-cost module comparable to the Arduino-Mega 2560 and can be used as Arduino-Mega 2560 in the Arduino-IDE. The Arduino bootloader is preloaded, hence the module is ready-to-use. The documentation shows the pin mapping of Arduino-naming to module pinout. Cuteduino: ATtiny85 Cytron Technologies: Cuteduino Features:
This sensor can also indicate that the vehicle is in a dangerous position. [6] Place 2 PCS on each adjacent side because it detect left and right/ front and back. A tilt sensor on a vehicle determines the orientation of the vehicle when it makes a tight turn or is in danger of tipping over. [7]
A lane detection system used behind the lane departure warning system uses the principle of Hough transform and Canny edge detector to detect lane lines from realtime camera images fed from the front-end camera of the automobile. A basic flowchart of how a lane detection algorithm works to help lane departure warning is shown in the figures.
An example algorithm for traffic-sign detection. Modern traffic-sign recognition systems are being developed using convolutional neural networks, mainly driven by the requirements of autonomous vehicles and self-driving cars. In these scenarios, the detection system needs to identify a variety of traffic signs and not just speed limits.