scholarly journals Development of a Raspberry Pi-Based Sensor System for Automated In-Field Monitoring to Support Crop Breeding Programs

Inventions ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. 42
Author(s):  
Worasit Sangjan ◽  
Arron H. Carter ◽  
Michael O. Pumphrey ◽  
Vadim Jitkov ◽  
Sindhuja Sankaran
Keyword(s):  
Real Time ◽  
Imaging System ◽  
Crop Growth ◽  
Sensor System ◽  
Plant Phenotyping ◽  
Raspberry Pi ◽  
The Internet ◽  
Growth Stages ◽  
Crop Breeding ◽  
Breeding Programs

Sensor applications for plant phenotyping can advance and strengthen crop breeding programs. One of the powerful sensing options is the automated sensor system, which can be customized and applied for plant science research. The system can provide high spatial and temporal resolution data to delineate crop interaction with weather changes in a diverse environment. Such a system can be integrated with the internet to enable the internet of things (IoT)-based sensor system development for real-time crop monitoring and management. In this study, the Raspberry Pi-based sensor (imaging) system was fabricated and integrated with a microclimate sensor to evaluate crop growth in a spring wheat breeding trial for automated phenotyping applications. Such an in-field sensor system will increase the reproducibility of measurements and improve the selection efficiency by investigating dynamic crop responses as well as identifying key growth stages (e.g., heading), assisting in the development of high-performing crop varieties. In the low-cost system developed here-in, a Raspberry Pi computer and multiple cameras (RGB and multispectral) were the main components. The system was programmed to automatically capture and manage the crop image data at user-defined time points throughout the season. The acquired images were suitable for extracting quantifiable plant traits, and the images were automatically processed through a Python script (an open-source programming language) to extract vegetation indices, representing crop growth and overall health. Ongoing efforts are conducted towards integrating the sensor system for real-time data monitoring via the internet that will allow plant breeders to monitor multiple trials for timely crop management and decision making.

scholarly journals Measurement of Environmentally Influenced Variations in Anthocyanin Accumulations in Brassica rapa subsp. Chinensis (Bok Choy) Using Hyperspectral Imaging

2021 ◽  
Vol 12 ◽  
Author(s):  
Hyo-suk Kim ◽  
Ji Hye Yoo ◽  
Soo Hyun Park ◽  
Jun-Sik Kim ◽  
Youngchul Chung ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Brassica Rapa ◽  
Environmental Conditions ◽  
Imaging System ◽  
Plant Phenotyping ◽  
Growth Stages ◽  
Anthocyanin Accumulation ◽  
Potential Health ◽  
Destructive Analysis ◽  
Leaf Tissues

Dietary supplements of anthocyanin-rich vegetables have been known to increase potential health benefits for humans. The optimization of environmental conditions to increase the level of anthocyanin accumulations in vegetables during the cultivation periods is particularly important in terms of the improvement of agricultural values in the indoor farm using artificial light and climate controlling systems. This study reports on the measurement of variations in anthocyanin accumulations in leaf tissues of four different cultivars in Brassica rapa var. chinensis (bok choy) grown under the different environmental conditions of the indoor farm using hyperspectral imaging. Anthocyanin accumulations estimated by hyperspectral imaging were compared with the measured anthocyanin accumulation obtained by destructive analysis. Between hyperspectral imaging and destructive analysis values, no significant differences in anthocyanin accumulation were observed across four bok choy cultivars grown under the anthocyanin stimulation environmental condition, whereas the estimated anthocyanin accumulations displayed cultivar-dependent significant differences, suggesting that hyperspectral imaging can be employed to measure variations in anthocyanin accumulations of different bok choy cultivars. Increased accumulation of anthocyanin under the stimulation condition for anthocyanin accumulation was observed in “purple magic” and “red stem” by both hyperspectral imaging and destructive analysis. In the different growth stages, no significant differences in anthocyanin accumulation were found in each cultivar by both hyperspectral imaging and destructive analysis. These results suggest that hyperspectral imaging can provide comparable analytic capability with destructive analysis to measure variations in anthocyanin accumulation that occurred under the different light and temperature conditions of the indoor farm. Leaf image analysis measuring the percentage of purple color area in the total leaf area displayed successful classification of anthocyanin accumulation in four bok choy cultivars in comparison to hyperspectral imaging and destructive analysis, but it also showed limitation to reflect the level of color saturation caused by anthocyanin accumulation under different environmental conditions in “red stem,” “white stem,” and “green stem.” Finally, our hyperspectral imaging system was modified to be applied onto the high-throughput plant phenotyping system, and its test to analyze the variation of anthocyanin accumulation in four cultivars showed comparable results with the result of the destructive analysis.

scholarly journals Sistem Kendali Dan Pengawasan Wilayah Pintu Berbasis IoT

2019 ◽  
Vol 2 (2) ◽  
pp. 101
Author(s):  
Arnes Sembiring
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Video Streaming ◽  
Streaming Video ◽  
Security System ◽  
Raspberry Pi ◽  
The Internet ◽  
Web Pages ◽  
Arduino Uno

Abstract - In this study, an IoT-based door security system was proposed which facilitated homeowners to open and close doors and unlock doors through the internet. The system is also equipped with a real time video streaming feature so that the owner can save the environment around the door and ensure the person at the door before opening it. The Raspberry Pi is used as the main controller of the system that provides web pages for users and signatories to access Arduino Uno boards. Arduino Uno controls the servo to control the door. The camera used in this study is a Raspberry Camera with 5 MP resolution. From the results of the tests carried out, the results of the system that have been made can work well. Expected full service and response to changes in users on web pages is also quite fast. Streaming video runs smoothly at 30 fps with a resolution of 640x480.Keywords - Raspberry Pi, Streaming Video, Internet of Things, Door Control 

scholarly journals Implementation of environmental monitoring based on KAA IoT platform

2020 ◽  
Vol 9 (6) ◽  
pp. 2578-2587
Author(s):  
M. Udin Harun Al Rasyid ◽  
M. Husni Mubarrok ◽  
Jauari Akhmad Nur Hasim
Keyword(s):  
Real Time ◽  
Ieee 802.15.4 ◽  
Data Transfer ◽  
Environmental Data ◽  
Experimental Result ◽  
Raspberry Pi ◽  
The Internet ◽  
Time Data ◽  
Iot Platform ◽  
Carbon Dioxide Co2

Wireless sensor network (WSN) is a key to access the internet of things (IoT). The popularity of IoT and the prediction that there will be more devices connected to the Internet cause difficulties in integrating and making connected devices. The problem of IoT implementation are the lack of real-time data collection, processing, and the inability to provide continuous monitoring. To overcome these problems, this paper proposes an IoT device for monitoring environmental conditions through the IoT KAA platform that can be monitored anywhere and anytime in real time. The end device node consists of several sensors such as as temperature, humidity, carbon monoxide (CO) and carbon dioxide (CO2) sensors. The collected data from the end device node will be transmitted via a communication based on IEEE 802.15.4 to Raspberry Pi gateway, then sent to the KAA cloud server and saved into the database. The environmental data can be accessed via a web-based sensor application. We Analize the performance evaluation in terms of transaction, availability, data transfer, response time, transaction rate, throughput, and concurrency. The experimental result shows that the use of KAA IoT platform is better than that without platform. 

scholarly journals A digital sensor to measure real-time leaf movements and detect abiotic stress in plants

2021 ◽  
Author(s):  
Geldhof Batist ◽  
Pattyn Jolien ◽  
Eyland David ◽  
Carpentier Sebastien ◽  
Van de Poel Bram
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Two Dimensions ◽  
Sensor System ◽  
Measurement Unit ◽  
Plant Phenotyping ◽  
Growth Responses ◽  
Plant Organ ◽  
Potential Applications ◽  
Leaf Movements

Abstract Plant and plant organ movements are the result of a complex integration of endogenous growth and developmental responses, partially controlled by the circadian clock, and external environmental cues. Monitoring of plant motion is typically done by image-based phenotyping techniques with the aid of computer vision algorithms. Here we present a method to measure leaf movements using a digital inertial measurement unit (IMU) sensor. The lightweight sensor is easily attachable to a leaf or plant organ and records angular traits in real-time for two dimensions (pitch and roll) with high resolution (measured sensor oscillations of 0.36° ± 0.53° for pitch and 0.50° ± 0.65° for roll). We were able to record simple movements such as petiole bending, as well as complex lamina motions, in several crops, ranging from tomato to banana. We also assessed growth responses in terms of lettuce rosette expansion and maize seedling stem movements. The IMU sensors are capable of detecting small changes of nutations (i.e., bending movements) in leaves of different ages and in different plant species. In addition, the sensor system can also monitor stress-induced leaf movements. We observed that unfavorable environmental conditions evoke certain leaf movements, such as drastic epinastic responses, as well as subtle fading of the amplitude of nutations. In summary, the presented digital sensor system enables continuous detection of a variety of leaf motions with high precision, and is a low-cost tool in the field of plant phenotyping, with potential applications in early stress detection.

scholarly journals THE ARCHITECTURE OF A STEREO IMAGE BASED SYSTEM TO MEASURE TREE GEOMETRIC PARAMETERS

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 183-189
Author(s):  
M. Bayat ◽  
H. Latifi ◽  
A. Hosseininaveh
Keyword(s):  
Real Time ◽  
Data Transfer ◽  
Imaging System ◽  
Three Dimensional ◽  
Point Clouds ◽  
Urban Trees ◽  
Stereo Image ◽  
Raspberry Pi ◽  
Remote Measurement ◽  
Dense Point

Abstract. Stereo photogrammetry enables collecting precise and detailed three-dimensional data of terrestrial objects. The estimation of qualitative and quantitative tree attributes, in particular those related to geometric measures, is crucial for forest management. In this study, a stereo imaging system is designed in order to measure a set of geometric attributes of urban trees such as crown dimensions, height and diameter at multiple height levels. The system consists of two hardware and software components. The hardware comprises two cameras with a specified baseline, two raspberry pi 3 model B+ boards, a GPS, an IMU and a power bank, all embedded in a box. The software includes a connection between the camera and the raspberry pi 3 in each side as well as data transfer to a laptop. The calibration is conducted in laboratory prior to applying the system and leads to achieve a disparity image from a pair of stereo imagery, which is then processed to extract dense point clouds. The system enables measuring basic, yet crucial tree attributes such as height and diameter in near real-time basis. The entire process is conducted by means of drastic libraries in Robot Operating System (ROS). Apart from being convenient and real-time, the system is associated with the potential for timely and precise measurements, which enable comparative analysis against other existing remote measurement systems as well as reference field data.

scholarly journals Mapping Crop Phenology in Near Real-Time Using Satellite Remote Sensing: Challenges and Opportunities

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Feng Gao ◽  
Xiaoyang Zhang
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Real Time ◽  
Land Surface ◽  
Vegetation Index ◽  
Growing Season ◽  
Crop Growth ◽  
Growth Stages ◽  
Crop Phenology ◽  
Crop Growth Stages

Crop phenology is critical for agricultural management, crop yield estimation, and agroecosystem assessment. Traditionally, crop growth stages are observed from the ground, which is time-consuming and lacks spatial variability. Remote sensing Vegetation Index (VI) time series has been used to map land surface phenology (LSP) and relate to crop growth stages mostly after the growing season. In recent years, high temporal and spatial resolution remote sensing data have allowed near-real-time mapping of crop phenology within the growing season. This paper summarizes two classes of near-real-time mapping methods, i.e., curve-based and trend-based approaches. The curve-based approaches combine the time series VIs and crop growth stages from historical years with the current observations to estimate crop growth stages. The curve-based approaches are capable of a short-term prediction. The trend-based approaches detect upward or downward trends from time series and confirm the trends using the increasing or decreasing momentum and VI thresholds. The trend-based approaches only use current observations. Both curve-based and trend-based approaches are promising in mapping crop growth stages timely. Nevertheless, mapping crop phenology near real-time is challenging since remote sensing observations are not always sensitive to crop growth stages. The accuracy of crop phenology detection depends on the frequency and availability of cloud-free observations within the growing season. Recent satellite datasets such as the harmonized Landsat and Sentinel-2 (HLS) are promising for mapping crop phenology within the season over large areas. Operational applications in the near future are feasible.

scholarly journals Sistem Monitoring Budidaya Ikan Lele Berbasis Internet Of Things Menggunakan Raspberry Pi

2018 ◽  
Vol 5 (6) ◽  
pp. 745 ◽  
Author(s):  
Erfan Rohadi ◽  
Dodik Widya Adhitama ◽  
Ekojono Ekojono ◽  
Rudy Ariyanto ◽  
Rosa Andrie Asmara ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Ph Sensor ◽  
Raspberry Pi ◽  
The Internet ◽  
Automation System ◽  
Mobile Web ◽  
And Control ◽  
Internet Of Things Technology ◽  
The Internet Of Things

<p><strong>Abstrak</strong><em><br /></em></p><p><em>Internet of Things</em> merupakan perkembangan teknologi berbasis internet masa kini yang memiliki konsep untuk memperluas manfaat yang benda yang tersambung dengan koneksi internet secara terus menerus. Sebagai contoh benda elektronik, salah satunya adalah Raspberry Pi. Teknologi ini memiliki kemampuan memberikan informasi secara otomatis dan <em>real time</em>. Salah satu pemanfaatan perkembangan teknologi ini di bidang perikanan adalah sistem pemantauan air kolam. Pada prakteknya, para pembudidaya ikan lele masih melakukan pemantauan tersebut secara konvensional yaitu dengan cara mendatangi kolam ikan. Hal ini berpengaruh terhadap efisiensi waktu dan keefektifan kerja pembudidayaan ikan.<strong></strong></p><p>Pada penelitian ini dikembangkan alat yang berfungsi untuk membantu memantau dan mengontrol kualitas air kolam ikan lele berbasis <em>Internet of Things</em>. Piranti yang diperlukan adalah sensor keasaman (pH), sensor suhu dan sebuah relay untuk mengatur aerator oksigen air. Data dari sensor-sensor tersebut direkam oleh Raspberry Pi untuk kemudian diolah menjadi informasi sesuai kebutuhan pengguna melalui perantara internet secara otomatis. Selanjutnya data-data tersebut dapat ditampilkan dengan berbagai macam platform, salah satunya dengan model <em>mobile web</em>.  <strong></strong></p><p>Hasil uji menunjukan bahwa pengembangan teknologi <em>Internet of Things</em>  pada sistem ini dapat membantu pembudidaya untuk melakukan pemantauan terhadap kualitas air secara otomatis. Sistem otomasi yang dikembangkan menjanjikan peningkatan keberhasilan dalam pembudidayaan ikan lele.</p><p> </p><p><em><strong>Abstract</strong></em></p><p><em>For recent years, the Internet of Things becomes the topic interest of improvement based on technologies that have the concept of extending the benefits of an object that is connected to an internet constantly. This technology has the ability to provide information automatically and real time. One of expansion in the field of fishery is the water ponds monitoring system. In the fact, the catfish farmers are still doing conventional monitoring by coming to the fish pond. This could affects the efficiency of time and effectiveness of fish cultivation work.</em></p><p><em>In this research, the systems that can monitor and control the quality of catfish water ponds based on the Internet of Things is proposed. The necessary tools are acidity sensor (pH), temperature sensor and a relay to adjust water oxygen aerator. The data sensors have been recorded by Raspberry Pi that processed into information according to user needs through internet automatically. Furthermore, these data have been displayed with a variety of platforms, one with a mobile web model.</em></p><p><em>The results shows that the system based on Internet of Things technology can monitor the water quality automatically. The automation system promises the productivity of catfish farming.</em></p>

scholarly journals Spatiotemporal Heterogeneity of Chlorophyll Content and Fluorescence Response Within Rice (Oryza sativa L.) Canopies Under Different Nitrogen Treatments

2021 ◽  
Vol 12 ◽  
Author(s):  
Jiafei Zhang ◽  
Liang Wan ◽  
C. Igathinathane ◽  
Zhao Zhang ◽  
Ya Guo ◽  
...  
Keyword(s):  
Oryza Sativa L ◽  
Plant Phenotyping ◽  
Growth Stages ◽  
Crop Breeding ◽  
Ojip Transient ◽  
Chlorophyll Content And Fluorescence ◽  
Vegetative Phase ◽  
Fluorescence Response ◽  
Vertical Heterogeneity ◽  
Spatiotemporal Heterogeneity

Accurate acquisition of plant phenotypic information has raised long-standing concerns in support of crop breeding programs. Different methods have been developed for high throughput plant phenotyping, while they mainly focused on the canopy level without considering the spatiotemporal heterogeneity at different canopy layers and growth stages. This study aims to phenotype spatiotemporal heterogeneity of chlorophyll (Chl) content and fluorescence response within rice leaves and canopies. Multipoint Chl content and high time-resolved Chl a fluorescence (ChlF) transient (OJIP transient) of rice plants were measured at different nitrogen levels and growth stages. Results showed that the Chl content within the upper leaves exhibited an increasing trend from the basal to the top portions but a decreasing pattern within the lower leaves at the most growth stages. Leaf Chl content within the rice canopy was higher in the lower leaves in the vegetative phase, while from the initial heading stage the pattern gradually reversed with the highest Chl content appearing in the upper leaves. Nitrogen supply mainly affects the occurrence time of the reverse vertical pattern. This could be the result of different nutritional demands of leaves transforming from sinks to sources, and it was further confirmed by the fall of the JI phase of OJIP transient in the vegetative phase and the rise in the reproductive phase. We further deduced that the vertical distribution of Chl content could have a defined pattern at a specific growth stage. Furthermore, the reduction of end acceptors at photosystem I (PSI) electron acceptor side per cross section (RE0/CS) was found to be a potential sensitive predictor for identifying the vertical heterogeneity of leaf Chl content. These findings provide prior knowledge on the vertical profiles of crop physiological traits, which explore the opportunity to develop more efficient plant phenotyping tools for crop breeding.

PROTOTYPE ALAT PEMANTAU SALURAN AIR BAWAH TANAH DENGAN MENGGUNAKAN WEBCAM C170 BERBASIS RASPBERRY PI

2015 ◽  
Vol 1 (1) ◽  
pp. 37-45
Author(s):  
Irwansyah Irwansyah ◽  
Hendra Kusumah ◽  
Muhammad Syarif
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Public Awareness ◽  
Underground Water ◽  
Raspberry Pi ◽  
Laptop Computer ◽  
Web Browser ◽  
Disaster Monitoring ◽  
The Times ◽  
Human Desire

Along with the times, recently there have been found tool to facilitate human’s work. Electronics is one of technology to facilitate human’s work. One of human desire is being safe, so that people think to make a tool which can monitor the surrounding condition without being monitored with people’s own eyes. Public awareness of the underground water channels currently felt still very little so frequent floods. To avoid the flood disaster monitoring needs to be done to underground water channels.This tool is controlled via a web browser. for the components used in this monitoring system is the Raspberry Pi technology where the system can take pictures in real time with the help of Logitech C170 webcam camera. web browser and Raspberry Pi make everyone can control the devices around with using smartphone, laptop, computer and ipad. This research is expected to be able to help the users in knowing the blockage on water flow and monitored around in realtime.

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