Velocity analysis on moving objects detection using multi-scale histogram of oriented gradient

An autonomous car is a one-of-a-kind specimen in today's technology. It is an automatic system in which most of the duties that humans undertake in the car can be done automatically with minimum human supervision for road safety features. Moving automobile detections, on the other hand, are prone to more mistakes and can result in undesirable situations such as minor car wrecks. Moving vehicle identification is now done using high-speed cameras or LiDAR, for example, whereas self-driving cars are produced with deep learning, which requires much larger datasets. As a result, there may be greater space for improvement in the moving vehicle detection model. This research intends to create another moving car recognition model that uses multi-scale feature-based detection to improve the model's accuracy while also determining the maximum speed at which the model can detect moving objects. The recommended methodology was to create a lab-scale model that can be used as a guide for video and image capture on the lab-scale model, as well as the speed of the toy vehicles captured from the Arduino Uno machine before testing the car recognition model. According to the data, Multi-Scale Histogram of Oriented Gradient can recognize more objects than Histogram of Oriented Gradient with higher object identification accuracies and precision

Analysis of Rabin-p and HIME(R) encryption scheme on IoT platform

This paper focuses on the implementation and analysis of the performance of the Rabin-p encryption scheme on the microprocessor platform. Rabin-p is an asymmetric cryptosystem that comes with simpler cryptographic properties than the Rabin cryptosystem. Rabin-p encryptionhas yet been tested on any IoT platform. The study tries to analyze the Rabin-p behavior instead of the algorithm optimization itself on the IoT platform. The algorithm of Rabin-p tested by utilizing the C-programming and implemented on a microprocessor system namely Raspberry Pi 3 model B. The Raspberry Pi 3 can be a multi-sensor in an IoT environment. The Rabin-p runtime taken to encrypt and decrypt as well as the power consumption is then compared with the performance of another Rabin variant, the HIME(R) encryption scheme. The result shows Rabin-p encryption scheme runtime is faster at 50% and current withdraw less at 1.3% compared to HIME(R)