Flat-Field and Colour Correction for the Raspberry Pi Camera Module

The automobile industries are concentrating to develop the design for self-driving cars. Nowadays they are many possibilities to implement the automated vehicle, but the drawbacks for implementing are also very high. In this paper, the miniature model of self-driving robot is created and demonstrated using the Raspberry pi with supporting sensors and motor drivers. So, this was mainly because of the security concerns that have raised in the initial testing stages. So, this paper could best describe an application that deals with the safety measures of the autonomous vehicles that are going to be dealt with in the nearer future. This paper tells us about how an application can be implemented using Raspberry Pi, camera module and the ultrasonic Sensor. Considering the different features and the cost, on a small scale a two-wheel vehicular robotic prototype has been designed. In the Autonomous car Raspberry pi is the central processor. Different type of images are captured by the camera module, and if these images have captured the color of traffic lights, then if the captured image is of the Red light then the motors of the vehicle should stop such that breaks of the car in real world should work. If the captured image is of Green light then the motors of the car should run and the vehicle should start to move in the direction it want to move and also using the Ultrasonic sensor if any of the objects that are nearby to the vehicle, then the vehicle should change the direction from which it is moving and this is well described throughout the paper.

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Robotic Search and Rescue using Human Detection System

Turkish Journal of Computer and Mathematics Education (TURCOMAT) ◽

10.17762/turcomat.v12i1s.1600 ◽

2021 ◽

Vol 12 (1S) ◽

pp. 162-169

Author(s):

Golande Avinash L, Et. al.

Keyword(s):

Detection System ◽

Search And Rescue ◽

Human Detection ◽

Raspberry Pi ◽

Human Being ◽

Technological Advancement ◽

Human Beings ◽

Camera Module ◽

Live Image

In this Technological advancement period, advanced construction improvements lead the formation of skyscrapers and homes which expanded the dangers of losing life because of natural and manmade catastrophes. In this system, we are proposing a radio-controlled bot that can identify live human beings from which are in the inaccessible region. Python libraries are used in Raspberry Pi microcontroller having Camera module to catch pictures of objects around it. This paper discusses about the mentioned system. The project takes live image samples and sends it to a network where this images can be accessed through a device. This images can be used for human detection. PIR sensor is used for the detection of human being trapped under debris. Whenever a human is detected the bot will send GPS co-ordinates to the device.

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Energy Efficacious IoT Based Nifty Parking Information System

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.c8644.019320 ◽

2020 ◽

Vol 9 (3) ◽

pp. 3151-3156

Keyword(s):

Information System ◽

Traffic Management ◽

Recognition Algorithm ◽

Energy Utilization ◽

Raspberry Pi ◽

License Plate ◽

Parking Space ◽

Rfid Tag ◽

Camera Module ◽

Mode Of Transportation

Urbanization has inflated populace. This has upsurged traffic and pollution turning traffic management into a tangible reality. Gazillions of people around the globe prefer ownership of private vehicles over public mode of transportation. There is an imbalance between the available parking space and demand. The proposed Internet-of-Things (IoT) based nifty parking information system (IPIS) module is deployed on-site to monitor vehicles, signal the availability of parking space to the user, facilitate reservation of the parking slot and thereby reduce the time in finding the parking slot. MIT App Inventor creates applications on Android operating system to facilitate slot reservation for authenticated users. IPIS integrates IoT based Raspberry Pi module with the mobile Application to design an eased parking system operable with minimal energy. The user details are recorded in a server database. Based on this, an RFID tag permits user entry and exit into the parking slot. A Raspberry-Pi(R-Pi) camera module captures the license plate image and uses image recognition algorithm to match the license plate of the vehicle with the database, authenticates and then allows the member to park his vehicle in the respective slot. IPIS provides highly secured, double verified user vehicle authentication. The Raspberry- Pi also adjusts the intensity of the lights using machine learning based on the density of the traffic recorded by the camera module. This research focuses on slot reservation for authenticated users, providing map guidance to the booked slot, maximizing slot utilization, facilitating with vehicle and user timestamp transit details in real time for surveillance, conserving parking slot light energy utilization while regulating the cars through parking spaces and also performs predictive analysis on evaluating the optimum distance between the camera and number plate for recognition and power dissipation.

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RASPBERRY PI SEBAGAI PEMANTAU RUANG LABORATORIUM MENGGUNAKAN METODE PEREKAMAN TERJADWAL BERBASIS DATABASE

Jurnal Teknik Ilmu Dan Aplikasi ◽

10.33795/jtia.v9i1.6 ◽

2021 ◽

Vol 9 (1) ◽

pp. 24-27

Author(s):

Usman Zulhijah Muhammad ◽

Eko Pamuji

Keyword(s):

Higher Education ◽

Raspberry Pi ◽

Personal Property ◽

Left Behind ◽

Camera Module ◽

Record Data ◽

Pi System

Practicum activities in higher education especially in State Polytechnic of Malang are generally carried out in a laboratory and based on a predetermined schedule. In the practicum activities are usually used equipment and practical materials borrowed by students from cabinets or warehouses for storage of tools and materials. In addition, in the laboratory where the practicum is carried out there are equipment and personal belongings belonging to students or teachers. From the experience that has happened, some campus-owned lab equipment and materials have been damaged and lost, or the personal property of students or teachers who have been left behind and even lost. Monitoring and recording using ordinary cameras has a disadvantage, that is, we cannot adjust the recording schedule that changes every day based on the space usage schedule. And record data is still one part or not grouped based on space usage schedule. Therefore, it is necessary to make a system that can monitor and record the process of laboratory practicum activities based on space usage schedule. In this study a system will be made using the embeded Raspberry Pi system and a camera module with MySQL as the database, this system is designed and created so that it can be used to record the laboratory practicum activities based on the space usage schedule in the database

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Iot Based Emergency Security System for Women

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.f4034.059720 ◽

2020 ◽

Vol 9 (7) ◽

pp. 233-236

Keyword(s):

Mobile Apps ◽

Text Messages ◽

Security System ◽

Raspberry Pi ◽

Night Time ◽

Live Video ◽

Police Station ◽

Camera Module ◽

Crimes Against Women ◽

Eve Teasing

In today’s era, women are progressing and scaling the peaks of success. However, there’s a significant hike in the number of crimes against women like molestation, eve-teasing, trafficking, etc. Also, there have been numerous attempts to ensure the safety of women ranging from the infamous mobile apps to the hefty belts &safety jackets,etc. However, it is not practical to carry such bulky systems and the victim may not be able to reach the smartphone without being noticed by the assaulter.This increases the risk factor. Therefore, to ensure the security of women, in this paper we propose an IOT based Emergency security system. This system includes a gsm, gps, raspberry pi, fingerprint module, camera module and IR led blasters. It aims at providing a dual security to the women with the help of panic button and fingerprint scanning device. Whenever a woman feels like she is in danger, she can manually switch on the system which will require her to scan her fingerprint for every 1 min. Practically, if she is in distress situation she would fail to scan and the camera module which is embedded in the woman’s pendant will start capturing images and live video. The GPS module will trace the exact location & GSM module will send emergency text messages to the specified contacts and alert the nearby police station. An additional provision of improved vision during night time using IR led blasters is incorporated in this system.

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A COMPARISON OF LOW-COST CAMERAS APPLIED TO FIXED MULTI-IMAGE MONITORING SYSTEMS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b2-2020-1033-2020 ◽

2020 ◽

Vol XLIII-B2-2020 ◽

pp. 1033-1040

Author(s):

N. Bruno ◽

K. Thoeni ◽

F. Diotri ◽

M. Santise ◽

R. Roncella ◽

...

Keyword(s):

Reference Model ◽

Low Cost ◽

Three Dimensional ◽

Laser Scanner ◽

Digital Camera ◽

Reconstruction Error ◽

Raspberry Pi ◽

Camera Systems ◽

Camera Module ◽

Image Monitoring

Abstract. Photogrammetry is becoming a widely used technique for slope monitoring and rock fall data collection. Its scalability, simplicity of components and low costs for hardware and operations makes its use constantly increasing for both civil and mining applications. Recent on site permanent installation of cameras resulted particularly viable for the monitoring of extended surfaces at very reasonable costs. The current work investigates the performances of a customised Raspberry Pi camera module V2 system and three additional low-cost camera systems including an ELP-USB8MP02G camera module, a compact digital camera (Nikon S3100) and a DSLR (Nikon D3). All system, except the Nikon D3, are available at comparable price. The comparison was conducted by collecting images of rock surfaces, one located in Australia and three located in Italy, from distances between 55 and 110 m. Results are presented in terms of image quality and three dimensional reconstruction error. Thereby, the multi-view reconstructions are compared to a reference model acquired with a terrestrial laser scanner.

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