Board Computer Raspberry Pi Research Articles

Implementation of Autonomous Driving on RC-CAR with Raspberry PI and AI Server

A lot of research is being done on autonomous driving vehicles or robots that recognize objects and drive themselves without human intervention. In order to develop autonomous driving technology, there is a fundamental difficulty in securing expensive real cars equipped with various sensors. In this paper, an autonomous driving system development platform was developed using an inexpensive RC-Car, and a test system that can test various algorithms related to autonomous driving was introduced. In the system developed in this study, the single board computer Raspberry PI was mounted on the RC-Car to control the car, and the autonomous driving-related algorithms were implemented in a separate AI server, and they communicated with the message-based ROS protocol. In addition, those who want to develop an autonomous driving system can easily attach desired sensors to the RC-Car, increasing scalability. In this paper, almost all algorithms related to autonomous driving have been implemented. A simple autonomous driving RC-Car system was actually implemented and operation was verified by designing and implementing algorithms such as lane recognition, driving along the lane, obstacle detection and stopping, traffic light recognition, driving between smooth and sharp curves, and autonomous parking. In sharp curves, the angle of the lane was tracked in a short period to prevent the vehicle from crossing the lane. In addition, we developed an Android app that can manually control the car and monitor the video from the camera in time. This study presented and solved various difficulties that could not be known by developing an autonomous driving algorithm using simulators.

Camera Based Smart Surveillance System

This paper is the survey of Smart camera based surveillance monitoring system using Raspberry pi. Camera based surveillance is important in all sectors, they can be colleges and hospitals, shopping malls and other challenging indoor and outdoor environments require high end cameras. This paper focus on low-cost project on single board computer Raspberry Pi. This is new technology and far less expensive and, it is being used as a main platform for video detection and acquisition. It can be used with involvement of mobile network (internet) to provide essential security and surveillance to our properties and for other control applications. The security system records information and transmits it via network to a Smart Phone using web application Raspberry pi.

Assessment of low-cost wireless sensors for structural health monitoring applications

Abstract Structural Health Monitoring (SHM) programs play an essential task in the field of civil engineering, especially for assessing safety conditions involving large structures such as viaducts, bridges, stadiums, and tall buildings. In fact, some of these structures are monitored 24 hours a day, 7 days a week, to supply dynamic measurements that can be used for the identification of structural problems, e.g., presence of cracks, excessive vibration, damage, among others. SHM programs may provide automated assessment of structural health by processing vibration data obtained from sensors attached to the structure. Frequently, SHM uses wired systems, which are usually expensive due to the necessity of continuous maintenance and are not always suitable for sensing remote structures. Conversely, commercial wireless systems often demand high implementation costs. Hence, this paper proposes the use of a low-cost wireless sensing system based on the single board computer Raspberry Pi, which significantly reduces implementation expenses while keeping data’s integrity. The wireless communication is performed in real-time through a local wireless network, responsible for sending and receiving vibration data. The proposed system is validated by comparing its results with a commercial wired system through a series of controlled experimental applications. The results suggest that the proposed system is suitable for civil SHM applications.

STEREO VISION APPLYING OPENCV AND RASPBERRY PI

Abstract. This article points out the single board computer Raspberry Pi and the related camera modules for image acquisition. Particular attention is directed to stereoscopic image recording and post processing software applying OpenCV. A design of a camera network is created and applied to a field application. The OpenCV computer vision library and its Python binding provides some script samples to encourage users developing their own custom tailored scripts. Stereoscopic recording is intended for extended base lines without a mechanical bar. Image series will be taken in order to wipe out moving objects from the frames. And finally the NoIR camera made infrared photography possible with low effort. Computer, accupack and lens board are assembled in a 3D printed housing operated by a mobile device.

PERANCANGAN SISTEM DETEKSI OBJEK PADA ROBOT KRSBI BERBASIS MINI PC RASPBERRY PI 3

KRSBI Wheeled is One of the competitions on the Indonesian Robot Contest,. It is a football match that plays 3 robot full autonomous versus other teams. The robot uses a drive in the form of wheels that are controlled in such a way, to be able to do the work the robot uses a camera sensor mounted on the front of the robot, while for movement in the paper author uses 3 omni wheel so the robot can move in all directions to make it easier towards the ball object. For the purposes of image processing and input and output processing the author uses a Single Board Computer Raspberry PI 3 are programmed using the Python programming language with OpenCV image processing library, to optimize the work of Single Board Computer(SBC) Raspberry PI 3 Mini PC assisted by the Microcontroller Arduino Mega 2560. Both devices are connected serially via the USB port. Raspberry PI will process the image data obtained webcam camera input. Next, If the ball object can be detected the object's position coordinates will be encoded in character and sent to the Microcontroller Arduino Mega 2560. Furthermore, Arduino mega 2560 will process data to drive the motors so that can move towards the position of the ball object. Based on the data from the maximum distance test results that can be read by the camera sensor to be able to detect a ball object is �5 meters with a maximum viewing angle of 120 �.

Development of a Hardware and Software System for Meteorological Observations

Article is devoted to development of a hardware and software system for monitoring of weather conditions. The hardware of this complex is the Arduino platform, which are connected sensors of temperature, humidity, atmospheric pressure, speed and direction of wind, level of ultra-violet radiation, which allow to watch environment parameters. Data are transferred to the remote server which is constructed on the basis of the single board computer Raspberry Pi, by means of a radio channel. For ensuring functioning of a complex, the software was written and it consisting of three programs. The first program was written to on Si similar language for operation of the Arduino controller. The second from programs was written for functioning of the server, it consists of MySQL DBMS, a script for data record in a basis and the PhpMyAdmin servers for administration of a DB. The third was written in the C# programming language and represents the application Windows forms. The made experiment showed that the complex allows to carry continuously meteorological observations, at the same time data remain in the database and the consumer software allows to carry their processing.

Developing a controller for registering passenger flow of public transport for the "smart" city system

A structure of the controller for registering passenger flow of public transport was developed, which includes the single board computer Raspberry Pi; GSM module; GPS module; controller of battery powered device; controller of the emergency restart of the device; button for registering passengers enjoying privileges; camera for registering passengers enjoying privileges and camera for registering passenger flow in a transportation vehicle. A built structure is characterized by the modular organization, which makes it possible to quickly upgrade the designed device. An algorithm of functioning of the controller of registering passenger flow of public transport and specialized software for implementing the functions of the controller were developed. A special feature of the software is the possibility of expanding functionality of the designed device in the process of upgrading the controller. Programming of the microcontroller was perforned in the language C, and programming of the controller based on Raspberry Pi 2 Model B was performed in Python. We built a model of functioning of the controller based on the Petri networks, which allows exploring dynamics of the system and identifying all possible states of the designed system. Authors developed technical support of the controller for registering passenger flow of public transport on the base of the single board computer Raspberry Pi, which ensures competitive price and the required functionality of the project solution. The resulting technical solution in the form of the controller for registering passenger flow of public transport of the system for managing transport flows of a smart city is characterized by low cost, required accuracy of calculating passengers and is the optimal project solution with wide functional capacities. The designed device was implemented and tested at the auto transportation enterprises Mens-Auto and Etalon in Ternopil (Ukraine).

IJARCCE - Computer and Communication Engineering

Video Surveillance is important as far as security is concerned these days. Commercial spaces, schools and hospitals, warehouses and other challenging indoor and outdoor environments require high end cameras with PTZ. The current technologies require RFIDs which are costly and hence the security domain in all becomes expensive. This paper describes the use of low cost single -board computer Raspberry Pi which follows face detection algorithm written in Python as a default programming environment. This new technology is less expensive and in this paper it is used as a standalone platform for hosting image processing. The paper aims at developing a system which captures real time images and displays them on browser using TCP/IP. The algorithm for face detection is being implemented on raspberry pi which enables live video streaming along with detection of human faces.

Improved Crypto Analysis for Scrambling Digital Video Using Secret Key

In the modern technology world, information security is very essential to communicate the confidential data between the networks. The cryptography is used to data transmission, information storage and also useful for system communication. for that, we implemented a high speed AES algorithm in order to provide the high security, reliability, safety for the transmitted data. The video is converted to image frames, then is converted to the VHDL codes in the MATLAB 2014a.The AES algorithm is used for transmitting the text, images, videos with available key values of the 128,198,256 bits. But, here the security is implemented with 128 key values of the AES algorithm for video cryptography in the VHDL implementation. The proposed system of the algorithm provides the high processing speed in the order of ps(>6800ps). The algorithm is implemented in ModelSim-Altera 6.3g_p1 (Quartus II 8.1) Web Edition. The video cartography is processed in video size of 8Mbps. The encryption and decryption is processed in VHDL with the digital output.Finally, the video is viewed by the single board computer Raspberry pi.