scholarly journals Plant Leaf Detection and Counting in a Greenhouse during Day and Nighttime Using a Raspberry Pi NoIR Camera

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6659
Author(s):  
Aryuanto Soetedjo ◽  
Evy Hendriarianti
Keyword(s):  
Execution Time ◽  
Low Cost ◽  
Infrared Camera ◽  
Raspberry Pi ◽  
Camera System ◽  
Detection And Counting ◽  
Outdoor Environments ◽  
Static Images ◽  
Leaf Detection ◽  
Non Destructive

A non-destructive method using machine vision is an effective way to monitor plant growth. However, due to the lighting changes and complicated backgrounds in outdoor environments, this becomes a challenging task. In this paper, a low-cost camera system using an NoIR (no infrared filter) camera and a Raspberry Pi module is employed to detect and count the leaves of Ramie plants in a greenhouse. An infrared camera captures the images of leaves during the day and nighttime for a precise evaluation. The infrared images allow Otsu thresholding to be used for efficient leaf detection. A combination of numbers of thresholds is introduced to increase the detection performance. Two approaches, consisting of static images and image sequence methods are proposed. A watershed algorithm is then employed to separate the leaves of a plant. The experimental results show that the proposed leaf detection using static images achieves high recall, precision, and F1 score of 0.9310, 0.9053, and 0.9167, respectively, with an execution time of 551 ms. The strategy of using sequences of images increases the performances to 0.9619, 0.9505, and 0.9530, respectively, with an execution time of 516.30 ms. The proposed leaf counting achieves a difference in count (DiC) and absolute DiC (ABS_DiC) of 2.02 and 2.23, respectively, with an execution time of 545.41 ms. Moreover, the proposed method is evaluated using the benchmark image datasets, and shows that the foreground–background dice (FBD), DiC, and ABS_DIC are all within the average values of the existing techniques. The results suggest that the proposed system provides a promising method for real-time implementation.

scholarly journals Inexpensive, scalable camera system for tracking rats in large spaces

2018 ◽  
Author(s):  
Rajat Saxena ◽  
Warsha Barde ◽  
Sachin S. Deshmukh
Keyword(s):  
Tracking System ◽  
Low Cost ◽  
Video Tracking ◽  
Recording System ◽  
Raspberry Pi ◽  
Camera Tracking ◽  
Camera System ◽  
Wireless Recording ◽  
Firing Characteristics ◽  
Improved Accuracy

AbstractMost studies focused on understanding the neural circuits underlying spatial navigation are restricted to small behavioral arenas (≤ 1 m2) because of the limits imposed by the cables extending from the animal to the recording system. New wireless recording systems have significantly increased the recording range. However, the size of arena is still constrained by the lack of a video tracking system capable of monitoring the animal’s movements over large areas integrated with these recording systems. We developed and benchmarked a novel, open-source, scalable multi-camera tracking system based on commercially available and low-cost hardware (Raspberry Pi computers and Raspberry Pi cameras). This Picamera system was used in combination with a wireless recording system for characterizing neural correlates of space in environments of various sizes up to 16.5 m2. Spatial rate maps generated using the Picamera system showed improved accuracy in estimating spatial firing characteristics of neurons compared to a popular commercial system, due to its better temporal accuracy. The system also showed improved accuracy in estimating head direction cell tuning as well as theta phase precession in place cells. This improved temporal accuracy is crucial for accurately aligning videos from multiple cameras in large spaces and characterizing spatially modulated cells in a large environment.

scholarly journals AutoTriage - An Open Source Edge Computing Raspberry Pi-based Clinical Screening System

2020 ◽  
Author(s):  
Chaitra Hegde ◽  
Zifan Jiang ◽  
Pradyumna Byappanahalli Suresha ◽  
Jacob Zelko ◽  
Salman Seyedi ◽  
...  
Keyword(s):  
Open Source ◽  
Low Cost ◽  
Characteristic Curve ◽  
Rapid Assessment ◽  
Infrared Camera ◽  
Visible Spectrum ◽  
Wait Time ◽  
Far Infrared ◽  
Raspberry Pi ◽  
Body Parts

AbstractWith the recent COVID-19 pandemic, healthcare systems all over the world are struggling to manage the massive increase in emergency department (ED) visits. This has put an enormous demand on medical professionals. Increased wait times in the ED increases the risk of infection transmission. In this work we present an open-source, low cost, off-body system to assist in the automatic triage of patients in the ED based on widely available hardware. The system initially focuses on two symptoms of the infection fever and cyanosis. The use of visible and far-infrared cameras allows for rapid assessment at a 1m distance, thus reducing the load on medical staff and lowering the risk of spreading the infection within hospitals. Its utility can be extended to a general clinical setting in non-emergency times as well to reduce wait time, channel the time and effort of healthcare professionals to more critical tasks and also prioritize severe cases.Our system consists of a Raspberry Pi 4, a Google Coral USB accelerator, a Raspberry Pi Camera v2 and a FLIR Lepton 3.5 Radiometry Long-Wave Infrared Camera with an associated IO module. Algorithms running in real-time detect the presence and body parts of individual(s) in view, and segments out the forehead and lip regions using PoseNet. The temperature of the forehead-eye area is estimated from the infrared camera image and cyanosis is assessed from the image of the lips in the visible spectrum. In our preliminary experiments, an accuracy of 97% was achieved for detecting fever and 77% for the detection of cyanosis, with a sensitivity of 91% and area under the receiver operating characteristic curve of 0.91. Heart rate and respiratory effort are also estimated from the visible camera.Although preliminary results are promising, we note that the entire system needs to be optimized before use and assessed for efficacy. The use of low-cost instrumentation will not produce temperature readings and identification of cyanosis that is acceptable in many situations. For this reason, we are releasing the full code stack and system design to allow others to rapidly iterate and improve the system. This may be of particular benefit in low-resource settings, and low-to-middle income countries in particular, which are just beginning to be affected by COVID-19.

scholarly journals Low-Cost Sensor Based on SDR Platforms for TETRA Signals Monitoring

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3160
Author(s):  
Robert Helbet ◽  
Paul Bechet ◽  
Vasile Monda ◽  
Simona Miclaus ◽  
Iulian Bouleanu
Keyword(s):  
Software Defined Radio ◽  
Dynamic Range ◽  
Low Cost ◽  
Frequency Resolution ◽  
Raspberry Pi ◽  
Maximum Speed ◽  
Control Module ◽  
Time Frequency ◽  
Global Positioning ◽  
Outdoor Environments

The paper presents the design and implementation of an electromagnetic field monitoring sensor for the measurement of the Terrestrial Truncked Radio (TETRA) signals using low-cost software defined radio (SDR) platforms. The sensor includes: an SDR platform, a Global Positioning System (GPS) module and a hardware control module. Several SDR platforms having different resolutions of the analog–digital converters were tested in the first phase. The control module was implemented in two variants: a fixed one, using a laptop, and a mobile one, using a Raspberry Pi. The tests demonstrate the following achieved performances: instantaneous acquisition band of 5.12 MHz; dynamic range of the input signal level of (−100 to −30) dBm; frequency resolution of 2.5 kHz; portability and flexibility for use in outdoor environments. The sensor allows complete reporting through amplitude-time-frequency-location descriptors, and in the case of the mobile version, the system performs correctly even at a maximum speed of displacement of 120 km/h. The price of the mobile sensor system variant is approximately EUR 320.

scholarly journals Camera Based Smart Surveillance System

2021 ◽  
Vol 9 (5) ◽  
pp. 48-51
Author(s):  
Mukul Singh ◽  
Md Nawaj Khan ◽  
Mohammad Makki ◽  
Md Irshad ◽  
Manohar Hussain ◽  
...  
Keyword(s):  
Web Application ◽  
Low Cost ◽  
New Technology ◽  
Smart Phone ◽  
Mobile Network ◽  
Raspberry Pi ◽  
Shopping Malls ◽  
Smart Surveillance ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments

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.

scholarly journals Infrared thermography used for composite materials

2018 ◽  
Vol 191 ◽  
pp. 00011
Author(s):  
Abdelaziz Mouahid
Keyword(s):  
Composite Materials ◽  
Infrared Thermography ◽  
Low Cost ◽  
Turbine Blades ◽  
Infrared Camera ◽  
Unit Weight ◽  
Material Surface ◽  
Wind Turbine Blades ◽  
Active Thermography ◽  
Non Destructive

Many areas of the industry use composite materials, because of their good mechanical features in terms of low density and high mechanical strength. Composite materials are used wherever elevated rigidity and strength with reduced unit weight are required; such as wind turbine blades, shipbuilding, aeronautical and aerospace. However, the properties of composites can be hugely affected because of inside defaults such as delaminations or local cracks. Several non-destructive methods have been used for the verification of defects during construction or operation, such as ultrasound or x-ray. These methods are costly and difficult to implement. Non-destructive method using infrared thermography is considered very useful and works perfect with low cost. Two methods of non-destructive detection by infrared exists, which are (i) passive thermography, that consists of measuring infrared stream emitted by the material and (ii) active thermography, which consists of heating the material and measuring the cooling of material surface using an infrared camera. This communication describes the basic principles of both passive and active thermography, and then describes other different methods for detection of composite materials defects.

Fault Localization of Power-Ground Short via Signal Injection and Oscilloscope Technique

2010 ◽  
Author(s):  
Binh Nguyen
Keyword(s):  
Low Cost ◽  
Short Circuit ◽  
Fault Localization ◽  
Fault Isolation ◽  
Test Apparatus ◽  
Good Working ◽  
Signal Injection ◽  
Set Up ◽  
Non Destructive ◽  
Short Circuit Condition

Abstract For those attempting fault isolation on computer motherboard power-ground short issues, the optimal technique should utilize existing test equipment available in the debug facility, requiring no specialty equipment as well as needing a minimum of training to use effectively. The test apparatus should be both easy to set up and easy to use. This article describes the signal injection and oscilloscope technique which meets the above requirements. The signal injection and oscilloscope technique is based on the application of Ohm's law in a short-circuit condition. Two experiments were conducted to prove the effectiveness of these techniques. Both experiments simulate a short-circuit condition on the VCC3 power rail of a good working PC motherboard and then apply the signal injection and oscilloscope technique to localize the short. The technique described is a simple, low cost and non-destructive method that helps to find the location of the power-ground short quickly and effectively.

scholarly journals Supermicrosurgical Suture-Stent Technique for A Lymphaticovenular Bypass

2021 ◽  
Vol 10 (12) ◽  
pp. 2595
Author(s):  
Ryo Karakawa ◽  
Hidehiko Yoshimatsu ◽  
Keisuke Kamiya ◽  
Yuma Fuse ◽  
Tomoyuki Yano
Keyword(s):  
Lower Extremity ◽  
Success Rate ◽  
Infrared Camera ◽  
Conventional Technique ◽  
Minimal Risk ◽  
Exclusion Criteria ◽  
Back Wall ◽  
Camera System ◽  
Good Patency

Background: Lymphaticovenular anastomosis (LVA) is a challenging procedure and requires a sophisticated supermicrosurgical technique. The aim of this study was to evaluate and establish a discrete supermicrosurgical anastomosis method using the “suture-stent technique”. Methods: Forty-eight LVA sites of twenty patients with lower extremity lymphedema who had undergone LVA between July 2020 and January 2021 were included in this study. LVA was performed with the conventional technique or with the suture-stent technique. The patency of the anastomoses was evaluated using an infrared camera system intraoperatively. The success rate on the first try and the final success rate for each group were compared. Results: After full application of the exclusion criteria, 35 LVAs of 16 patients including 20 limbs were included in the analysis. The ratio of good patency findings after anastomosis in the suture-stent technique group was 100%. The incidences of leakage or occlusion on the first try were statistically greater in the conventional technique group (29.4%) than in the suture-stent technique group (0%) (p = 0.0191). All anastomoses achieved good patency in the final results. Conclusion: With its minimal risk of catching the back wall during the anastomosis, the suture-stent technique can be considered an optimal anastomosis option for LVA.

scholarly journals The grades and freshness assessment of eggs based on density detection using machine vision and weighing sensor

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Supakorn Harnsoongnoen ◽  
Nuananong Jaroensuk
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Measuring System ◽  
Coefficient Of Determination ◽  
Water Displacement ◽  
Non Invasive ◽  
Future Potential ◽  
Non Destructive ◽  
Egg Freshness

AbstractThe water displacement and flotation are two of the most accurate and rapid methods for grading and assessing freshness of agricultural products based on density determination. However, these techniques are still not suitable for use in agricultural inspections of products such as eggs that absorb water which can be considered intrusive or destructive and can affect the result of measurements. Here we present a novel proposal for a method of non-destructive, non-invasive, low cost, simple and real—time monitoring of the grading and freshness assessment of eggs based on density detection using machine vision and a weighing sensor. This is the first proposal that divides egg freshness into intervals through density measurements. The machine vision system was developed for the measurement of external physical characteristics (length and breadth) of eggs for evaluating their volume. The weighing system was developed for the measurement of the weight of the egg. Egg weight and volume were used to calculate density for grading and egg freshness assessment. The proposed system could measure the weight, volume and density with an accuracy of 99.88%, 98.26% and 99.02%, respectively. The results showed that the weight and freshness of eggs stored at room temperature decreased with storage time. The relationship between density and percentage of freshness was linear for the all sizes of eggs, the coefficient of determination (R2) of 0.9982, 0.9999, 0.9996, 0.9996 and 0.9994 for classified egg size classified 0, 1, 2, 3 and 4, respectively. This study shows that egg freshness can be determined through density without using water to test for water displacement or egg flotation which has future potential as a measuring system important for the poultry industry.

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