Wireless telemetry system of an Off-Road vehicle

Telematics Smart Testing and Validation Tool

Rapid advancements in the field of embedded systems have facilitated the development of cost-effective complex projects with innovative outcomes. These advancements also apply for the automotive racing domain in the form of digital data extraction and wireless communication. It is of utmost importance to have a system in racing vehicles that will cater real-time data to the race engineers using which the process of troubleshooting the vehicle in the pit can be aided. In this manuscript, a data logging and a telemetry system for an All-Terrain Vehicle (ATV) has been developed by Team Torpedo, the ATV racing team of Amrita School of Engineering, Coimbatore. The team participates in national amateur off-road racing competitions that see an attendance of over 250 reputed college teams from different parts of the country. This system is based on a low-cost embedded platform powered by an Arduino Mega 2560 microcontroller. Important parameters like speed, G forces, GPS coordinates, etc. are logged in a microSD card which is used for validating the ATVs design and standardize its performance. During the racing events, the collected data is wirelessly transmitted to the pit using the Zigbee protocol over a reasonably large distance. In the receiver's end, the data is graphically rendered for the race engineers to assess the ATV's real-time performance.

Low-cost data logging and telemetry system for All-Terrain Vehicle performance analysis

In the modern era of computers, various new technologies have been arising. One such thing is a touchless application that is used or controlled aerially with hand gestures and movements. Augmented reality and virtual reality have come into use which is controlled by gesture controls. Applications that work with gesture controls have started targeting all kinds of users. Python libraries like MediaPipe and OpenCV are used in hand-tracking, palm detection and object detection. Our work aims in developing a virtual painter that helps young children to draw simple images and shapes of varying sizes. The tool recognizes the hand with hand and palm detector models of MediaPipe and capture the modes for selection and drawing using OpenCV library. In the covid pandemic where children are stuck at home and everything has become online, this tool helps them in practicing simple shapes virtually and also makes it interesting for them. The system is tested by drawing aerially with hands and using selection/drawing modes. It worked well with less time latency due to the inbuilt SSD algorithm used in MediaPipe.

Hand Tracking Based Human-Computer Interaction Teaching System

Driver drowsiness is one of the leading causes of accidents and has become a hot research topic. This paper gives an overview of detecting the drowsiness of drivers using behavioral metrics and machine learning approaches. The face imparts a great deal of information (eye blinks, head motions, etc.) which can be utilized to deduce sleepiness. By recognizing the driver's drowsiness and notifying the driver, Computer vision techniques and Image processing technologies can minimize most accidents. This research addresses the issue by identifying key factors such as eye closure, yawning, and head orientation. To determine this, Recurrent Neural Network (RNN) and classifiers were used to extract the facial landmarks, and a 3D locator was used for estimation. In many ways, the culminating results suggest that the real-time approach's performance outperforms the older approach.

Real- Time Driver Drowsiness Detection System using Facial Landmarks

As there are increasing demand for communication system and storage systems in the modern world there can be errors such as soft errors during the data transmission between the communication system. Combining error correction and detection algorithms can give great dependability in data transmission and storage systems. The error detection and correction of the design is done using Ternary content addressable memory and a Cyclic redundancy check module from an SRAM. The scenario in this case is that when the data is commuted into the memory from any communication system its prone to soft errors over time or any external factors. The errors occurring must be reduced at any cost so the proposed system consists of the TCAM module that checks the memory with the given address in which the data is stored in the memory one after the other during the write operation of the memory. Once the write operation. A CRC module also adds to the system for the read operation for the error correction just in case of occurrence of error during the read operation. The designing of the module is done with Verilog HDL using ModelSim and the implementation of the schematics is done with Xilinx Vivado. This error detection and correction can help in detecting the error during the read and write operation ensuring the data integrity twice and there would be less chances for an error to occur.

Prabhu E

Papers

Low-cost data logging and telemetry system for All-Terrain Vehicle performance analysis

Hand Tracking Based Human-Computer Interaction Teaching System

Real- Time Driver Drowsiness Detection System using Facial Landmarks

Error Resolving in SRAM Emulated FPGA using CRC