Design and development of object detection and separation mechanism using Raspberry PI

2020 ◽  
Author(s):  
Vinaykumar Patancheru ◽  
G. Shravan Kumar ◽  
S. Venkata Surya Prasad
Keyword(s):  
Object Detection ◽  
Raspberry Pi ◽  
Separation Mechanism ◽  
Design And Development ◽  
Detection And Separation

scholarly journals Design and Development of Bionic Eye for Visually Challenged People using Raspberry Pi Processor

2021 ◽  
Vol 12 (3) ◽  
pp. 3437-3443
Author(s):  
P.Lavanya Et.al
Keyword(s):  
Object Detection ◽  
Learning Algorithm ◽  
Recognition Rate ◽  
Ultrasonic Sensor ◽  
Gradient Algorithm ◽  
Raspberry Pi ◽  
Design And Development ◽  
Object A ◽  
Bionic Eye ◽  
Visually Challenged

Bionic Eye will play a major role in the future development of visually challenged people. This research focuses on design and development of Bionic Eye to detect the hurdles for visually challenged people. This intelligence system uses the shape and movement of an object for detection and tracking. The object recognition rate is improved with the help of Stochastic Decent Gradient algorithm. Raspberry Pi is the processor used for the Bionic Eye as it gives out command on the object detection and the data from the camera is collected and then transmitted to the system. The distance and object movement is obtained by ultrasonic sensor. The range of the ultrasonic sensor is set and the distance is measured. A camera is used for capturing the object. A voice output saying “there is an object in front of you” is heard after an object is detected. The accuracy of the object detection is obtained by the deep learning algorithm. Increasing the recognition rate is the main advantage over object detection systems

scholarly journals IoT-based Pet Feeding Robot Design and Development

2021 ◽  
Vol 9 (VI) ◽  
pp. 3637-3644
Author(s):  
P. Ajay
Keyword(s):  
Body Weight ◽  
Remote Control ◽  
Internet Of Things ◽  
Raspberry Pi ◽  
Robot Design ◽  
Design And Development ◽  
Pet Owners ◽  
At Home

Pets in the home need particular attention and care. They must be provided with food, beverages, and medicine as soon as possible. Due of most owners' hectic lifestyles, this job may not be as easy as anticipated. Inadequate attention to the requirements of pets may have serious consequences such as hunger and illness, among other things. In light of the above, this paper presents an Internet of Things-based automated feeder system that use the Raspberry Pi for remote control, scheduling, and intelligence. Its design and subsequent execution are anticipated to at least take care of the nutritional aspects of pets by delivering food, beverages, and medicine to pets on a schedule or as needed in the absence of the owner. As a result, the goal of this study is to automate the monitoring and feeding procedure, which is now done manually by pet owners. The four-wheeled system allows it to effortlessly climb stairs. Because of its body weight, the mechanism generates traction. The robot has applications such as remote feeding of every kind of animal from afar, remote exploration of the house to deceive thieves into believing someone is at home. It also lets you customise daily meals, keep your pet secure while you are away from home, store up to 7 pound, keep food fresh, and monitor your pet's nutrition. The robot may also prevent a person from eating a particular meal while allowing other animals to access the food. All these features attract owners of more than one animal to the robot.

scholarly journals Safety Assistance Visual Surveillance Robot

2020 ◽  
Vol 9 (5) ◽  
pp. 752-756
Keyword(s):  
High Risk ◽  
Object Detection ◽  
Radar System ◽  
Visual Surveillance ◽  
Human Interaction ◽  
Raspberry Pi ◽  
Live Streaming ◽  
Human Beings ◽  
Toxic Environment ◽  
Echo Time

There is a need for safety assistance visual surveillance that can be effectively used to navigate hazardous places which cannot be accessed by human beings. Several high-risk conditions like radioactive zone, toxic environment and accident-prone areas are usually approached/tackled by humans with little to no information about their conditions. Hence our aim is to reduce any human interaction with these unsafe circumstances by proposing a visual surveillance robot that is capable of moving in any terrain and can relay live information to the controller situated at a remote location. In this paper we address the implementation of Visual Surveillance bot by using a Camera that rotates at 360 degree with the help of DC motor, which illustrate the surrounding so as to provide the estimation of danger if any. We present the execution by efficiently live streaming information with the help of Raspberry pi and by using the MATLAB software to create a RADAR plot by analyzing the object detected by Ultrasonic sensor. The usage of MATLAB not only simplifies the analysis but also helps in creating an enhanced RADAR system by using an ARDUINO to support the ultrasonic system in recording the echo time and object detection angle.

scholarly journals DISAIN SISTEM OTOMASI SUHU RUANGAN PERTEMUAN DENGAN PENERAPAN TEKNIK MACHINE LEARNING

2019 ◽  
pp. 117-120
Author(s):  
Stephanie Imelda Pella ◽  
Hendro FJ L
Keyword(s):  
Machine Learning ◽  
Object Detection ◽  
Room Temperature ◽  
Cooling System ◽  
Raspberry Pi ◽  
Air Cooling ◽  
Minimum Value ◽  
Air Cooling System ◽  
Four Levels ◽  
And Control

This research presents an automation process of controlling room temperature based on the number of people detected in a room. The system consists of a single board raspberry pi computer, esp8266 micro controller, pi camera, and an infrared module. This research is divided into two parts, namely object detection using Raspbery Pi and Tensorflow and Open CV libraries and controlling air cooling system (ACS) using esp8266 and infrared modules by transmitting hexadecimal AC control codes. The ACS temperature is divided into four levels with a minimum value at 18o C and a maximum at 24o C. System testings were carried out in an empty room and a room with a capacity of 50 people that is fully occupied. The results show that the system is able to detect the number of people in the room and control the ACS, but under certain conditions some objects are not detected because the position and camera tilt is not optimal.

scholarly journals Faulty Lock Detection and Separation System

2019 ◽  
pp. 39-44
Author(s):  
Mishra Nikhilkumar N ◽  
Madale Kabirdas N ◽  
Khairnar Pratik S ◽  
Sangale Prasad M ◽  
Ostwal Rishabh S
Keyword(s):  
Separation Mechanism ◽  
Conveyer Belt ◽  
Separation System ◽  
Locking Mechanism ◽  
Good Reputation ◽  
Product Manufacturing ◽  
Rubber Belt ◽  
Is Design ◽  
Belt System ◽  
Detection And Separation

All product manufacturing units need to have a faulty product detection and separation system in order to maintain product quality and maintain a good reputation. So here we demonstrate such a system using a mini conveyer belt system. We propose to design and fabricate a faulty product detection and separation mechanism. Each product is different and thus has different mechanisms to detect faulty products. Here we detect fault in lock based on its size and operations. We use a sensor to detect each lock size and operations as products move over a conveyer belt. The conveyer is design so that it can hold the lock so that it does not fall or leave the conveyer belt. A defected product with size lower than minimum limit will be automatically detected as it moves on a conveyer belt and separated by a conveyer arm. If the product passes the size test the next sensor perform it task to operate the lock so that it can open the locking mechanism and check if it opens or not. If the product passes the test it is send for packaging and if not the product is separated and sent to production line for correct the fault. Here we use rollers and rubber belt to develop a mini conveyer belt mechanism. This mechanism is operated by a motor. This system uses servo motor arm to separate the faulty product.

scholarly journals A Research Paper on Traffic Sign Recognition with Machine Learning and IOT

2021 ◽  
Vol 9 (VI) ◽  
pp. 1774-1778
Author(s):  
Mahesh Singh
Keyword(s):  
Machine Learning ◽  
Object Detection ◽  
Real World ◽  
Research Paper ◽  
Raspberry Pi ◽  
Detection Accuracy ◽  
Great Success ◽  
The Real ◽  
Road Traffic Safety ◽  
Execution Speed

This paper will help to bring out some amazing findings about autonomous prediction and performing action by establishing a connection between the real world with machine learning and Internet Of thing. The purpose of this research paper is to perform our machine to analyze different signs in the real world and act accordingly. We have explored and found detection of several features in our model which helped us to establish a better interaction of our model with the surroundings. Our algorithms give very optimized predictions performing the right action .Nowadays, autonomous vehicles are a great area of research where we can make it more optimized and more multi - performing .This paper contributes to a huge survey of varied object detection and feature extraction techniques. At the moment, there are loads of object classification and recognition techniques and algorithms found and developed around the world. TSD research is of great significance for improving road traffic safety. In recent years, CNN (Convolutional Neural Networks) have achieved great success in object detection tasks. It shows better accuracy or faster execution speed than traditional methods. However, the execution speed and the detection accuracy of the existing CNN methods cannot be obtained at the same time. What's more, the hardware requirements are also higher than before, resulting in a larger detection cost. In order to solve these problems, this paper proposes an improved algorithm based on convolutional model A classic robot which uses this algorithm which is installed through raspberry pi and performs dedicated action.

Object Detection and seperation Using Raspberry PI

2018 ◽  
Author(s):  
Sumeet Sanjay Walam ◽  
Siddhi Prakash Teli ◽  
Bilal Sikandar Thakur ◽  
Ravindra Ramchandra Nevarekar ◽  
Suhas M Patil
Keyword(s):  
Object Detection ◽  
Raspberry Pi

scholarly journals Smart Hat for the blind with Real-Time Object Detection using Raspberry Pi and TensorFlow Lite

2021 ◽  
Author(s):  
Matshehla Konaite ◽  
Pius A. Owolawi ◽  
Temitope Mapayi ◽  
Vusi Malele ◽  
Kehinde Odeyemi ◽  
...  
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Raspberry Pi

scholarly journals Design and Development of an Intelligent System for Pothole and Hump Identification on Roads

2019 ◽  
Vol 8 (3) ◽  
pp. 5294-5300 ◽  
Keyword(s):  
Image Processing ◽  
Fuel Consumption ◽  
Intelligent System ◽  
Processing Technique ◽  
Simple Solution ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Ultrasonic Sensors ◽  
Design And Development ◽  
Geographical Position

Country’s economy depend on well-maintained roads as they are major means of transportation. It becomes essential to identify pothole and humps in order to avoid accidents and damages to the vehicles that is caused because of distress to drivers and also to save fuel consumption. In this regard, this work presents a simple solution to detect potholes and humps and hence avoid accidents and help drivers. Potholes are detected using Image Processing Technique and Ultrasonic Sensors are used to detect humps. Controlling device used is Raspberry Pi. The system acquires the geographical position of potholes using Wi-Fi and transmits it to authorities to take corrective measures

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