scholarly journals Automatic Fish Feeder System for Aquaponics using Wi-Fi Based WSN

2020 ◽  
Vol 8 (6) ◽  
pp. 835-840
Keyword(s):  
Mobile Application ◽  
Processing Technique ◽  
Food Delivery ◽  
Integrated System ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Identification System ◽  
Fish Feed ◽  
Fish Waste ◽  
Feeder Mechanism

Aquaponics is a farming method, which is the combination of aquaculture and hydroponics, which grows fish and plants together in one integrated system. The fish waste provides an organic food source for the plants, and the plants naturally filter the water for the fish. The purpose of this project is to build an automatic fish feeder system for aquaponics using image processing technique with the help of Wireless Sensor Network (WSN). This helps the farmers to reduce manual effort and safeguard a balanced food delivery. The number of fish in the pond may vary over time, so the amount of fish feed provided need to be changed. As there will be a large number of fish moving randomly in a pond, the manual tracking and counting of fish is very difficult. It is a time consuming and erroneous process. This work focuses on developing a system that tracks and counts the fish in the pond for aquaponics. This automatic fish identification system processes the video of the entire pond and makes it easier to estimate the count of fish. The frames from the video are processed using Raspberry-Pi board and the count of fish is transmitted through Wi-Fi. Such a system would assist to feed the fish accordingly. Based on the count transferred, a fish feeder mechanism is controlled using NodeMCU at the other end of the Wi-Fi. The amount of fish feed remaining in the feeding box is informed to the user through mobile application.

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

scholarly journals Eyeball Controlled Wheelchair

2020 ◽  
pp. 238-247
Keyword(s):  
Image Processing ◽  
The Elderly ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Indoor Space ◽  
Driver Circuit ◽  
The Individual ◽  
Driving Circuit ◽  
Eye Gesture

: A basic wheelchair is a gadget for people influenced by moderate, extreme physical incapacities and interminable disease. It is also meant for the elderly people. Many people with disabilities cannot manage the energized wheelchair operating joystick, sound, furthermore, hand developments as it is harder for the individual to do such specific tasks also it is programming focused. This strategy comprises of equipment which reduces the person's work utilizing the image processing method. This model comprised of a camera that tracks the eyeball movement and hence the position of the pupil by the image processing technique. And thereby the wheelchair is constrained by a user’s eye gesture in an indoor space. When the development has been initiated and it is given to the Raspberry pi for processing. The procedure relies on the feed coding and an output is given into the driver circuit. Likewise, the hindrance location sensors will be associated as an Emergency Brake that gives necessary conditions for the conventional activity of the wheelchair framework. Every one of the four wheels are associated with a driving circuit that moves the wheelchair

A Novel Approach of Controlling Stoppage of Drip Infusion Using Image Processing on Raspberry PI Platform

2021 ◽  
Vol 58 (S) ◽  
pp. 65-72
Author(s):  
Hartono Pranjoto ◽  
Lanny Agustine ◽  
Diana Lestariningsih ◽  
Yesiana Dwi Wahyu Werdani ◽  
Widya Andyardja ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Camera ◽  
Detection Algorithm ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Novel Approach ◽  
Pinch Valve ◽  
Canny Edge ◽  
Infusion Fluid

Intravenous drip diffusion is a common practice to treat patients in hospitals. During treatment, nurses must check the condition of the infusion bag frequently before running out of fluid. This research proposes a novel method of checking the infusion bag using an image processing technique on a compact Raspberry PI platform. The infusion monitoring system proposed here is based solely on capturing the image of the infusion bag and the accompanying bag/ tube. When the infusion fluid enters the patient, the surface of the liquid will decrease, and at the end will reach the bottom of the infusion bag. When the image of the fluid surface touches the bottom of the infusion bag, a mechanism will trigger a relay, and then activate a pinch valve to stop the flow of the infusion fluid before it runs out. The entire system incorporates a digital camera and Raspberry as the image processor. The surface of the liquid is determined using the Canny Edge Detection algorithm, and its relative position in the tube is determined using the Hough Line Transform. The raw picture of the infusion bag and the processed image are then sent via a wireless network to become part of a larger system and can be monitored via a simple smartphone equipped with the proper application, thus becoming an Internet of Things (IoT). With this approach, nurses can carry on other tasks in caring for the patients while this system substitutes some work on checking the infusion fluid.

scholarly journals Speedy Detection Module for Abandoned Belongings in Airport Using Improved Image Processing Technique

2021 ◽  
Vol 3 (4) ◽  
pp. 251-262
Author(s):  
A. Sathesh ◽  
Yasir Babiker Hamdan
Keyword(s):  
Image Processing ◽  
Video Surveillance ◽  
Extended Period ◽  
Processing Technique ◽  
Object Identification ◽  
Image Processing Technique ◽  
Identification System ◽  
Research Issues ◽  
Identification Approach ◽  
Edge Based

Recently, in computer vision and video surveillance applications, moving object recognition and tracking have become more popular and are hard research issues. When an item is left unattended in a video surveillance system for an extended period of time, it is considered abandoned. Detecting abandoned or removed things from complex surveillance recordings is challenging owing to various variables, including occlusion, rapid illumination changes, and so forth. Background subtraction used in conjunction with object tracking are often used in an automated abandoned item identification system, to check for certain pre-set patterns of activity that occur when an item is abandoned. An upgraded form of image processing is used in the preprocessing stage to remove foreground items. In subsequent frames with extended duration periods, static items are recognized by utilizing the contour characteristics of foreground objects. The edge-based object identification approach is used to classify the identified static items into human and nonhuman things. An alert is activated at a specific distance from the item, depending on the analysis of the stationary object. There is evidence that the suggested system has a fast reaction time and is useful for monitoring in real time. The aim of this study is to discover abandoned items in public settings in a timely manner.

scholarly journals Human Distance Estimation using Quadcopter for Surveillance Purpose

2019 ◽  
Vol 8 (12S2) ◽  
pp. 483-488
Keyword(s):  
Image Processing ◽  
Everyday Life ◽  
Unmanned Aerial Vehicles ◽  
Crime Rate ◽  
Processing System ◽  
Distance Estimation ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Aerial Vehicles

Nowadays, quadcopters are commonly used. Quadcopters are unmanned aerial vehicles with four propellers to provide lift to fly and hover above ground. Quadcopter nowadays is a very common commercial item in everyday life. Some quadcopters are designed to do 3D or 2D mapping of a certain area or to take videos or just for entertainment purposes. Quadcopter is a very versatile item and is able to change into anything for example a quadcopter can also be used for security purposes to decrease the crime rate of our country. The objective of this study is to design and develop a quadcopter with image processing system to have the ability to measure the distance of a human from the drone itself. The quadcopter is designed to be small in size and have a mini computer like Raspberry Pi on top of it to compute the algorithm to calculate the distance of the human by using image processing technique through the camera which is setup on the drone. Human detecting algorithm YOLO and software Open CV is chosen to detect human and calculate the distance from the quadcopter. The results show that the system is quite limited by the capabilities of the hardware. The system shows an accuracy of more than 90 percent when the human is standing within a certain range. Both the accuracy of the distance sensing and human recognizing system is affected by the limitation of the hardware.

scholarly journals Smart Leaf Recognition System

2020 ◽  
Vol 9 (5) ◽  
pp. 289-291
Keyword(s):  
Image Processing ◽  
Early Stage ◽  
Recognition System ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Plant Leaves ◽  
Plant Leaf ◽  
Automatic Technique

One of major issue nowadays is the agricultural productivity which is something our Nation’s economy highly depends. Technology based advancements may lead to detection of diseases in plants which are quite natural. Care should be taken in this area before it causes serious effects on plants which mainly affect the product quality, quantity or productivity. Early stage detection of diseases in plants through some automatic technique is beneficial as it reduces a huge work of monitoring in large acres of crops. When they appear on plant leaves, earlier detection helps us to increase the yield and productivity. This paper presents an algorithm for image processing technique which is used for automatic detection and classification of plant leaf diseases with the help of raspberry pi and sensors. This survey is about different diseases and its classification, techniques which are used for plant leaf disease detection and also its respective fertilizer sprayed on the leaves.

scholarly journals A Novel Approach to Detect Driver Drowsiness and Alcohol Intoxication using Haar Algorithm with Raspberry Pi

2020 ◽  
Vol 3 (9) ◽  
pp. 48-51
Author(s):  
M. Agna Manu ◽  
Dayana Jaijan ◽  
S. N. Nissa ◽  
S. Jesna ◽  
Abin Shukoor ◽  
...  
Keyword(s):  
Real Time ◽  
Detection System ◽  
Alcohol Intoxication ◽  
Drunk Driving ◽  
Research Area ◽  
Processing Technique ◽  
Road Accident ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Driver Drowsiness

Drowsiness in driver and alcohol consumption are the critical cause of road accident and death. Lives of pedestrian and passengers are put to risk as drivers tend to fall asleep and also when the driver is in his drunken state. Detection of driver drowsiness and its indication is an active research area now. There are 3 methods for detection of driver fatigue which includes vehicle-based method, behavioural method, and physiological based method. We adopt behavioural method. This project is aimed towards developing a prototype of drowsiness and alcohol detection system using Haar algorithm with raspberry pi. This project proposes a real time detection of driver’s drowsiness as well as alcohol intoxication and subsequently alerting them. The primary purpose of this drowsiness and alcohol detection system is to develop a system that can reduce the number of accidents from drowsiness and drunk driving of vehicle. It consists of camera which is placed in front of the driver to detect the face. An alcohol sensor which is a gas sensor used to sense the drinking state of driver. Haar algorithm is used for face detection. The results demonstrate the accuracy and robustness of the hybridized of image processing technique. Thus, it can be concluded the proposed approach is an effective solution for a real-time of driver drowsiness and alcohol detection.

scholarly journals Footprint-Based Health Monitoring Database using Raspberry PI

2020 ◽  
Vol 8 (6) ◽  
pp. 851-854
Keyword(s):  
Image Processing ◽  
Health Monitoring ◽  
Processing System ◽  
Processing Technique ◽  
Health Condition ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Data Allocation ◽  
Color Analysis ◽  
The Web

The health monitoring of the person can be done in the different ways. The health of the patient can be determined by the image processing technique. The biometric parameters can gather the details of the health condition of the patient. The digital image processing can be applied in the various filed such as medical, geology, research etc., In this paper they proposes the foot print technology this can capture the foot print of the patient by using the web cam. The captured image can be analyzed by using the shape and the dimension analysis. The foot print can reads the each person identity. Based upon the identity and the numbers the image processing system is implemented. It uses the raspberry pi as the main part. The data which is captured by the web cam can be stored in the SD card. The data allocation is done in the memory path. The classification of the data is takes place by using the data separation algorithm. The color analysis can takes place a significant place based upon the color we can able to classify the foot print and makes it for further analysis. There are several steps can be took place the image acquisition, edge detection, feature extraction, pattern recognition, pattern matching. The matched image can be provided as the better result. Based upon the result the health condition can be predicted. This method is highly effective and accurate when compared to other method

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