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Journal articles on the topic 'Plant Growth Monitoring'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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1

Ceulemans, R. J. "PLANT GROWTH OPTIMISATION BY PHOTOSYNTHETIC MONITORING." Acta Horticulturae, no. 174 (December 1985): 309–12. http://dx.doi.org/10.17660/actahortic.1985.174.39.

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2

Banke, Vedant. "IoT Enabled Plant Monitoring System." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 3247–50. http://dx.doi.org/10.22214/ijraset.2024.60455.

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Abstract: As due to tremendous growth in the field of IOT, this technology has became easier to use & implement.In this paper we have proposed a simple solution based on plant monitoring system. Plant Monitoring System is a crucial task for the betterment growth of the plants. In thisall the parameters which are required like soil moisture content, temperature, humidity are all the essential parameters which should be maintained and controlled to its utmost level.
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3

Murase, H., and Y. Nishiura. "FINITE ELEMENT RETINA FOR PLANT GROWTH MONITORING." Acta Horticulturae, no. 440 (December 1996): 401–6. http://dx.doi.org/10.17660/actahortic.1996.440.70.

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4

Kumar, Ranveer. "IOT BASED PLANT MONITORING SYSTEM." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem32765.

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The internet of things (IOT) has various use in Agriculture filed. Main moto is making IOT based Plant monitoring system is monitor plant growth system and control plant monitoring growth. In this system using DHT11 sensor, Touch sensor, soil moisture to monitor and collecting data. collect the data through the real time basic and send it through the cloud there is alert system if there anyone touches the plant then you have given an alert through an Alert Notification, On your mobile phone. there is one sensor dh11 to you know the real time temperature in what temperature is our environment i
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5

Schwartzkopf, Steven H. "A Nondestructive Method for Continuously Monitoring Plant Growth." HortScience 20, no. 3 (1985): 432–34. http://dx.doi.org/10.21273/hortsci.20.3.432.

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Abstract In the past, plant growth generally has been measured using destructive methods. This paper describes a nondestructive technique for continuously monitoring plant growth. The technique provides a means of directly and accurately measuring plant growth over both short and long time intervals. Application of this technique to the direct measurement of plant growth rates is illustrated using corn (Zea mays L.) as an example.
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admin, admin, Deepak S. Dharrao, Kapil Joshi, et al. "IoT-Enabled monitoring system for Plant Health Growth." Journal of Cybersecurity and Information Management 14, no. 1 (2025): 252–59. https://doi.org/10.54216/jisiot.140219.

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In current scenario, plant health monitoring plays a crucial role in effective health maintenance of plants in climate changes. Internet of Things (IoT) played an efficient role in realizing the remote and real-time monitoring of any physical things and activities through internet connectivity. In this study we have proposed a system that is able to monitor the plant health with the assimilation of wireless sensors and wireless network. The proposed system is able to log the sensor values on the plants on the cloud server through internet connectivity.
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7

Toda, S., T. Sakamoto, Y. Imai, et al. "Smartphone-based strawberry plant growth monitoring using YOLO." Acta Horticulturae, no. 1377 (October 2023): 69–76. http://dx.doi.org/10.17660/actahortic.2023.1377.8.

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8

Puri, Bhuvan. "IoT and AI-based Plant Monitoring System." International Journal of Machine Learning and Networked Collaborative Engineering 04, no. 03 (2020): 135–42. http://dx.doi.org/10.30991/ijmlnce.2020v04i03.005.

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Plants plays a vital role in the environment because it provides the health support through absorbing the carbon dioxide and releasing the oxygen to the atmosphere. Although, it required to maintain the proper plant growth and health as well as provide the appropriate monitoring. To overcome these concerns, an Artificial Intelligence (AI) and Internet of Things (IoT) based solution is proposed to monitor the plant’s growth and health. This study demonstrates the real-time monitoring of the plants via environmental sensors such as DHT 11 and soil moisture sensors. Real-time values stored in the
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9

Di Tocco, Joshua, Daniela Lo Presti, Carlo Massaroni, et al. "Plant-Wear: A Multi-Sensor Plant Wearable Platform for Growth and Microclimate Monitoring." Sensors 23, no. 1 (2023): 549. http://dx.doi.org/10.3390/s23010549.

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Wearable devices are widely spreading in various scenarios for monitoring different parameters related to human and recently plant health. In the context of precision agriculture, wearables have proven to be a valuable alternative to traditional measurement methods for quantitatively monitoring plant development. This study proposed a multi-sensor wearable platform for monitoring the growth of plant organs (i.e., stem and fruit) and microclimate (i.e., environmental temperature—T and relative humidity—RH). The platform consists of a custom flexible strain sensor for monitoring growth when moun
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10

Tong, Yin-Syuen, Tou-Hong Lee, and Kin-Sam Yen. "Deep Learning for Image-Based Plant Growth Monitoring: A Review." International Journal of Engineering and Technology Innovation 12, no. 3 (2022): 225–46. http://dx.doi.org/10.46604/ijeti.2022.8865.

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Deep learning (DL) approaches have received extensive attention in plant growth monitoring due to their ground-breaking performance in image classification; however, the approaches have yet to be fully explored. This review article, therefore, aims to provide a comprehensive overview of the work and the DL developments accomplished over the years. This work includes a brief introduction on plant growth monitoring and the image-based techniques used for phenotyping. The bottleneck in image analysis is discussed and the need of DL methods in plant growth monitoring is highlighted. A number of re
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11

Rantelobo, K., H. J. F. Lami, A. Sampeallo, C. Y. Solet, B. Bernandus, and A. C. Louk. "Video Transmission in Plant Growth Monitoring Systems Using IoT." IOP Conference Series: Earth and Environmental Science 1482, no. 1 (2025): 012025. https://doi.org/10.1088/1755-1315/1482/1/012025.

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Abstract This research focuses on video transmission analysis for plant growth monitoring using IoT (Internet of Things) technology. It contributes to videobased analysis of plant changes and growth using a frame-by-frame basis. The study introduces a novel IoT-based approach for monitoring land spinach plant growth (Kale - Ipomea Reptans Poir), utilizing ESP32-CAM combined with ImageJ software. The system provides a cost-effective, real-time solution for measuring plant leaf area, addressing the limitations of manual methods and expensive alternatives. This approach enhances agricultural moni
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12

Husin, Nor Maizatul Mona, Norazlin Ibrahim, and Hanisah Salam. "Development of Plant Growth Monitoring in Hydroponic Using Image Processing." Semarak International Journal of Agriculture, Forestry and Fisheries 4, no. 1 (2025): 46–58. https://doi.org/10.37934/sijaff.4.1.4658b.

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Hydroponics is a growing trend in agriculture in Asian countries. Ensure that the plant receives the proper concentration of nutrients solution, air temperature, light, and humidity for healthy plant grow. Lack of one of these factors may cause plants to be stunted and the production of crops to fail. The experiment conducted at two different places for environmental manipulation thus the plant growth observed. Direct measurement of plant growth usually destructive and can cause partial or whole plant damage. Image processing can be used to create an automated system for monitoring plant growt
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Toda, S., T. Higuchi, T. Sakamoto, et al. "Deep learning model for monitoring daily tomato plant growth." Acta Horticulturae, no. 1337 (March 2022): 283–88. http://dx.doi.org/10.17660/actahortic.2022.1337.38.

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14

Lubis, H., R. F. Rahmat, J. Karansa, and S. Purnamawati. "Monitoring System of Rice Plant Growth Using Microcontroller Sensor." Journal of Physics: Conference Series 1235 (June 2019): 012116. http://dx.doi.org/10.1088/1742-6596/1235/1/012116.

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15

Kecskés, Mihály L., Michael T. Rose, Erwin Michel, et al. "Rapid immuno-monitoring of inoculant plant growth-promoting microorganisms." Engineering in Life Sciences 9, no. 6 (2009): 431–36. http://dx.doi.org/10.1002/elsc.200800101.

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16

Awang Ahmad, Zahari, Tan Sie Chow, Mohamad Akmal Muhammad Asmawi, Abu Hassan Abdullah, and Ping Jack Soh. "Durian plant health and growth monitoring using image processing." Bulletin of Electrical Engineering and Informatics 14, no. 3 (2025): 1925–37. https://doi.org/10.11591/eei.v14i3.8550.

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The demand for durians has increased considerably, gaining significant popularity in the market. Under the Industrial Revolution 4.0, precision agriculture is expanding globally, utilizing a range of digital technologies to provide the farming industry with crucial information for enhancing farm productivity. For durians to produce high-quality fruit, it is essential that the plants receive sufficient nutrients. Therefore, it is crucial for farmers to monitor the growth rate of durian plants to ensure they receive suitable nutrients for optimum growth. Manual growth monitoring often yields ina
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17

Trihandoyo, Agus, and Nadia Rahmadina Aristawati. "Designing Plant Monitoring System Using Arduino." International Conference On Research And Development (ICORAD) 2, no. 1 (2023): 71–80. http://dx.doi.org/10.47841/icorad.v1i2.84.

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Plants, crops, and flowers are living organisms that contribute to the productivity and beauty of our planet. They require a healthy habitat that provides adequate light, air, temperature, water, and nutrients for optimal growth. However, many plants are unable to adjust to extreme changes in their environment, which can negatively impact their growth. Ensuring that plants have the proper habitat is essential for their well-being and success. Additionally, in times of water scarcity, it is important to use available water efficiently. To address this issue, an efficient automation system must
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18

Kunal, Kumar Sahu, Kumar Suyash, Taram Abhinay, Kumar Rana Danendra, and Anjum Naushin. "IOT-based smart plant monitoring system using NodeMCU." i-manager’s Journal on Electrical Engineering 17, no. 2 (2023): 27. http://dx.doi.org/10.26634/jee.17.2.20483.

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The Internet of Things (IoT) is transforming the agriculture industry and enabling farmers to contend with the enormous challenges they face. Livestock monitoring, conservation monitoring, and plant & soil monitoring are the challenges for which IoT can provide solutions. Innovative IoT applications address agricultural issues, enhancing the quality, quantity, sustainability, and cost-effectiveness of production. Today's large and local farms can leverage IoT to remotely monitor sensors detecting soil moisture, crop growth, pests, and control smart connected harvesters and irrigation equip
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19

Kharraz, Nezha, and István Szabó. "Monitoring of plant growth through methods of phenotyping and image analysis." Columella : Journal of Agricultural and Environmental Sciences 10, no. 1 (2023): 49–59. http://dx.doi.org/10.18380/szie.colum.2023.10.1.49.

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With the rapid development of imaging technology, computing power, and algorithms, computer vision has revolutionized thoroughly plant phenotyping and is now a major tool for phenotypic analysis. Those reasons constructed the base for developing image-based plant phenotyping methods, it is a priority for the complementary or even alternative to the manual measurement. Nonetheless, the use of computer vision technology to analyze plant phenotypic traits can be affected by a lot of factors such as research environment, imaging system, and model selection. The field of plant phenotyping is develo
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20

Mohabuth, Abdool Qaiyum, and Devashish Nem. "An IoT-Based Model for Monitoring Plant Growth in Greenhouses." Journal of Information Systems and Informatics 5, no. 2 (2023): 536–49. http://dx.doi.org/10.51519/journalisi.v5i2.489.

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The unstable climatic conditions are promoting the adoption of smart agriculture. The introduction of IoT technology in the cultivation process allows for the monitoring and control of plant growth through automation. While the traditional greenhouse system is already an upgrade to the traditional cultivation system, it still has room for improvement with the integration of technology. The traditional greenhouse system requires close monitoring of growth rates through manual intervention and can be prone to various hazards. Incorrect interpretations of plant requirements can result in wrong in
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21

Xu, Haoyan, Guangyao Zhang, Wensheng Wang, et al. "A Highly Sensitive, Low Creep Hydrogel Sensor for Plant Growth Monitoring." Sensors 24, no. 19 (2024): 6197. http://dx.doi.org/10.3390/s24196197.

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Ion−conducting hydrogels show significant potential in plant growth monitoring. Nevertheless, traditional ionic hydrogel sensors experience substantial internal creep and inadequate sensitivity, hindering precise plant growth monitoring. In this study, we developed a flexible hydrogel sensor composed of polyvinyl alcohol and acrylamide. The hydrogel sensor exhibits low creep and high sensitivity. Polyvinyl alcohol, acrylamide, and glycerol are crosslinked to create a robust interpenetrating double network structure. The strong interactions, such as van der Waals forces, between the networks mi
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22

Xiao, Qian Hu, Shao Jie Weng, and Wen Qing Zhang. "Monitoring System for Plant Growth Environment Based on Zigbee/RS485." Applied Mechanics and Materials 511-512 (February 2014): 381–84. http://dx.doi.org/10.4028/www.scientific.net/amm.511-512.381.

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After studying the research status of monitoring system for plant growth information, a system is developed with Kingview, VB and C to monitor soil temperature, soil moisture, air temperature, air humidity, Illumination and carbon dioxide. The system realizes real time monitoring, remote access, trend analysis and many other functions. Transmission distance is estimated by channel transmission loss model. Theoretical transmission distances are 1691.99m outdoor and 480.84m indoor. The real transmission distance is measured in the production base. The experimental communication distances are 168
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23

Bhavikatti, Sujata, Sadanand P, Mukta Patil, Vibhuti Pradeep, and Shailaja S.Mudengudi. "Automated Roof Top Plant Growth Monitoring System in Urban Areas." International Journal of Engineering and Manufacturing 9, no. 6 (2019): 14–23. http://dx.doi.org/10.5815/ijem.2019.06.02.

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24

Thakur, Divyansh, Yugal Kumar, Arvind Kumar, Pradeep Kumar, and Vijendra Singh. "Real Time Monitoring of Valeriana Jatamansi Plant for Growth Analysis." Procedia Computer Science 132 (2018): 507–17. http://dx.doi.org/10.1016/j.procs.2018.05.003.

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25

Krishnen, Ganisan, Mihály L. Kecskés, Michael T. Rose, et al. "Field monitoring of plant-growth-promoting rhizobacteria by colony immunoblotting." Canadian Journal of Microbiology 57, no. 11 (2011): 914–22. http://dx.doi.org/10.1139/w11-059.

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Inoculant plant-growth-promoting bacteria are emerging as an important component of sustainable agriculture. There is a need to develop inexpensive methods for enumerating these organisms after their application in the field, to better understand their survival and impacts on yields. Immunoblotting is one potential method to measure viable cells, but the high cost of the conventionally used nylon membranes makes this method prohibitive. In this study, less expensive alternative materials such as filter papers, glossy photo papers, and transparencies for the purpose of colony immunoblotting wer
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26

Tabacco, M. B., Q. Zhou, and T. G. DiGiuseppe. "Optical sensors for monitoring and control of plant growth systems." Advances in Space Research 14, no. 11 (1994): 223–26. http://dx.doi.org/10.1016/0273-1177(94)90301-8.

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27

Punsala S.M.P., Benthara B.W.H.T, Ferdinando D.V.P., Chathura W.B.D., Silva S., and Liyanage R. "IoT based Plant Growth and Health Monitoring System for Mushrooms." International Journal of Engineering and Management Research 13, no. 4 (2023): 33–40. http://dx.doi.org/10.31033/ijemr.13.4.4.

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This research paper proposes the development of an IoT-based monitoring system using a robot camera for mushroom cultivation in Sri Lanka. The system aims to address several sub-objectives, including harvest time prediction, disease detection, quality assurance, and environmental monitoring. The research utilizes image processing and machine learning techniques to capture mushroom images, analyze their size, shape, morphology, and color, and predict the optimal harvest time. It also focuses on identifying common diseases, researching their early symptoms, and recommending appropriate treatment
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Nurhasan, Usman, Arief Prasetyo, Gilang Lazuardi, Erfan Rohadi, and Hendra Pradibta. "Implementation IoT in System Monitoring Hydroponic Plant Water Circulation and Control." International Journal of Engineering & Technology 7, no. 4.44 (2018): 122. http://dx.doi.org/10.14419/ijet.v7i4.44.26965.

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Hydroponics is the cultivation of plants by utilizing water without using soil by emphasizing the fulfillment of nutritional needs for plants. Deep Flow Technic (DFT) is a type of hydroponics that implements a continuous flow of nutrients and there is a pool of half of the diameter of the pipe that inundates the roots of the plant. A common obstacle experienced by DFT is the lack of maintenance of plant growth elements such as water circulation, light intensity, temperature, humidity and pH of the water which causes these plants not to grow optimally. Then it is necessary to monitor and contro
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29

Kim, Young-Choon, Moon-Taek Cho, and Hae-Jong Joo. "A Study on the Development of Plant Growth Monitoring System Using Plant Measurement Algorithms." Journal of the Korea Academia-Industrial cooperation Society 13, no. 6 (2012): 2702–6. http://dx.doi.org/10.5762/kais.2012.13.6.2702.

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30

Coles, Graeme D., D. J. Abernethy, Mary C. Christey, A. J. Conner, and B. K. Sinclair. "Monitoring hairy-root growth by image analysis." Plant Molecular Biology Reporter 9, no. 1 (1991): 13–20. http://dx.doi.org/10.1007/bf02669285.

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31

Wang, Xiu Qing, Xu Qie, Chun Xia Zhang, and Na Zhao. "Research of Video Surveillance and Diagnosis System for Plant Diseases Based on DM6446." Applied Mechanics and Materials 373-375 (August 2013): 892–96. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.892.

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TMS320DM6446 was used as a platform to build a video monitoring and controlling system for plant diseases. TMS320DM6446 can capture and encode the plant video. It delivered the video stream to the PC monitoring center by using streaming technology. Monitoring center displayed the received video, monitored the plant condition of growth and disease, and then obtained the image and relevant characteristics of disease. It used a combination of neural networks and expert systems to diagnose the plant diseases, and gave the control methods. The experimental results show that the proposed system can
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32

Mochida, Keiichi, Ryuei Nishii, and Takashi Hirayama. "Decoding Plant–Environment Interactions That Influence Crop Agronomic Traits." Plant and Cell Physiology 61, no. 8 (2020): 1408–18. http://dx.doi.org/10.1093/pcp/pcaa064.

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Abstract To ensure food security in the face of increasing global demand due to population growth and progressive urbanization, it will be crucial to integrate emerging technologies in multiple disciplines to accelerate overall throughput of gene discovery and crop breeding. Plant agronomic traits often appear during the plants’ later growth stages due to the cumulative effects of their lifetime interactions with the environment. Therefore, decoding plant–environment interactions by elucidating plants’ temporal physiological responses to environmental changes throughout their lifespans will fa
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33

Mohamed Mydin M. Abdul Kader, Muhammad Naufal Mansor, Zol Bahri Razali, et al. "Environmental Lighting towards Growth Effect Monitoring System of Plant Factory using ANN." Journal of Advanced Research in Applied Sciences and Engineering Technology 43, no. 2 (2024): 167–77. http://dx.doi.org/10.37934/araset.43.2.167177.

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Malaysia is currently driven to become another most developed country in the world. Among other priority sector is Food Sustainability. Along the process, our vegetable supply-demand keeps increasing by year. Compared to traditional systems, closed systems or its other name called hydroponic is getting more important for plant production, with artificial light which has many potential advantages, including better quality transplants, shorter production time and less resource use. To gain full profit from it, the quality of vegetables needs to be controlled efficiently. Climate conditions, espe
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C N, Asha, Sheetal N, Divya G G, and Chandhini Kumari Arpitha M R. "Smart Hydroponic System for Petroselinum Crispum Growth Monitoring with Nutrition Automation." IRO Journal on Sustainable Wireless Systems 6, no. 4 (2025): 342–52. https://doi.org/10.36548/jsws.2024.4.005.

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Hydroponics is a technique of growing plants using a water-based nutrient solution rather than soil and is well suited for small farmers, hobbyists, and commercial enterprises. It involves growing plants in a nutrient solution with or without a soilless substrate for physical support. A hydroponic system is an essential component of a plant factory. By using fewer resources, hydroponics is seen as a more sustainable option than traditional agriculture. This proposed study aims to provide a brief overview of hydroponic systems based on existing research and suggest an approach to enhance real-t
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35

WASSEL, OSAMA M. M. "MONITORING PLANT GROWTH AND YIELD PRODUCTION IN SOME EGYPTIAN COTTON CULTIVARS USING PLANT MAP DATA." Egyptian Journal of Agricultural Research 79, no. 3 (2001): 1019–39. http://dx.doi.org/10.21608/ejar.2001.320025.

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36

Lakshmi, K., and S. Gayathri. "Implementation of IoT with Image processing in plant growth monitoring system." Journal of Scientific and Innovative Research 6, no. 2 (2017): 80–83. http://dx.doi.org/10.31254/jsir.2017.6208.

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An automated system for monitoring the growth of plant can be done with appropriate taxonomies. Such kind of information can be useful for formers, botanists, industrialists, food engineers and physicians. This work combines Image Processing and IoT to monitor the plant and to collect the environmental factors such as humidity and temperature. In image processing, a recognition system capable of identifying plants by using the images of their leaves has been developed and with the help of the images use of pesticides can be controlled. The system runs pre-processing and feature extraction tech
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Lee, Cheng-Ju, Ming-Der Yang, Hsin-Hung Tseng, Yu-Chun Hsu, Yu Sung, and Wei-Ling Chen. "Single-plant broccoli growth monitoring using deep learning with UAV imagery." Computers and Electronics in Agriculture 207 (April 2023): 107739. http://dx.doi.org/10.1016/j.compag.2023.107739.

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38

Narula, Gita Batra, Kiran Soni, Alka B. Vadakan, et al. "Bio-organic approach for monitoring the Plant growth for Sustainable agriculture." Journal of Agriculture and Applied Biology 4, no. 2 (2023): 161–73. http://dx.doi.org/10.11594/jaab.04.02.06.

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Agriculture plays a critical role in sustaining life and driving the economy of India. The idea of sustainable agriculture is a holistic approach to meet the demands of food supply while protecting our environment. Through various sources, it has been found out that the country is running out of the main reservoirs of water to irrigate the fields. The present study investigated the possibility to prepare different natural hydrogels using Chia seeds, Flax seed, Gond katira, Arrowroot powder, Tapioca, Agar-agar, Corn starch, Gelatin, Aloe vera, and their comparison with a synthetic hydrogel used
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39

Thirrunavukkarasu, R. R., M. Deepika, R. Dharshini, A. Infant Shiny, and S. Karthiga. "Smart Farming for Efficient Crop Growth." ACS Journal for Science and Engineering 3, no. 2 (2023): 36–43. http://dx.doi.org/10.34293/acsjse.v3i2.83.

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India largely depends on the agriculture sector. Besides, agriculture is not just a mean of livelihood but a way of living life in India. India is heavily dependent on the agricultural sector. Moreover, farming is not just a livelihood in India, it is a way of life. Crop monitoring plays an important role in controlling various pests, weeds or diseases in crops. This provides information about the current state of the crop and anticipates time to predict what the next crop problem will be. Improper management and protection of crops causes more infections and affects overall production. Some f
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40

C, Arunkumar. "Smart Irrigation System Using Moisture Level Sensor." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 2383–86. http://dx.doi.org/10.22214/ijraset.2023.52040.

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Abstract: Farming is the cultivation of plants and livestock. Plant monitoring is one of the most important tasks in farming. The goal of this paper is to use IoT in the NodeMCU system platform for plant monitoring and smart gardening. The primary goal of this paper is to reduce direct interaction and provide comfort to the farmer by improving the system's overall performance. Humidity, sunlight, and soil moisture are important factors to consider when monitoring plant productivity. Plant growth and health information must be provided to the user on a continuous basis by monitoring and recordi
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41

Abdul Rani, Abdul Ismail, Bryan Jong Li Zhe, Nur’ain Farhah Suhardi, et al. "Integrated Vertical Aquaponics Monitoring System using Hibiscus Sense with Favoriot Platform." Journal of Advanced Research in Applied Mechanics 135, no. 1 (2025): 97–105. https://doi.org/10.37934/aram.135.1.97105.

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Aquaponics combines aquaculture and hydroponics, where fish and aquatic animals are grown in conjunction with soil-less plant cultivation in a circulated environment. Vertical aquaponics typically utilizes the nutrient film technique (NFT) method, employing pipes to continuously stream water to each channel, providing nutrients, water, and oxygen to the plants. This project aims to develop a real-time monitoring system for the vertical aquaponics setup, using Hibiscus Sense along with Arduino Mega to measure pH, total dissolved solids (TDS), and water temperature to establish the optimal condi
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Abdul Rani, Abdul Ismail, Bryan Li Zhe Jong, Nur’ain Farhah Suhardi, et al. "Integrated Vertical Aquaponics Monitoring System using Hibiscus Sense with Favoriot Platform." Journal of Advanced Research Design 135, no. 1 (2025): 77–87. https://doi.org/10.37934/ard.135.1.7787.

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Aquaponics combines aquaculture and hydroponics, where fish and aquatic animals are grown in conjunction with soil-less plant cultivation in a circulated environment. Vertical aquaponics typically utilizes the nutrient film technique (NFT) method, employing pipes to continuously stream water to each channel, providing nutrients, water and oxygen to the plants. This project aims to develop a real-time monitoring system for the vertical aquaponics setup, using Hibiscus Sense along with Arduino Mega to measure pH, total dissolved solids (TDS) and water temperature to establish the optimal conditi
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43

Shabana, Naaz, and Wallure Vijaykumar. "IoT-Enabled Real-Time Crop Monitoring Systems." International Journal of Computer Science (IIJCS), A Peer reviewed Refereed Research Journal 6, no. 7 (2018): 76–84. https://doi.org/10.5281/zenodo.14922271.

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Nowadays, IoT based remote sensing is one of the largest growing modern technologies which is widely used in smart farming. IoT based remote sensing systems in smart farming handle the various agriculture tasks like soil sensing, temperature sensing, humidity and weather sensing, light sensing, and anomalies detect sensing in a smarter and efficient way for better productivity. IotT based remote sensing system for smart farming is suitable for plant monitoring to check the soil conditions as well as other factors which may help to start a better growth of a plant. It may support efficient usag
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Zhang, He, Yuan, Liu, Zhou, and Huang. "Machine Learning-Based Spectral Library for Crop Classification and Status Monitoring." Agronomy 9, no. 9 (2019): 496. http://dx.doi.org/10.3390/agronomy9090496.

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The establishment and application of a spectral library is a critical step in the standardization and automation of remote sensing interpretation and mapping. Currently, most spectral libraries are designed to support the classification of land cover types, whereas few are dedicated to agricultural remote sensing monitoring. Here, we gathered spectral observation data on plants in multiple experimental scenarios into a spectral database to investigate methods for crop classification (16 crop species) and status monitoring (tea plant and rice growth). We proposed a set of screening methods for
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45

Lavenia, Tanashia, and Fahmy Rinanda Saputri. "Blynk App-Based Plant Monitoring System Design." International Journal of Science and Environment (IJSE) 3, no. 4 (2023): 145–50. http://dx.doi.org/10.51601/ijse.v3i4.82.

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Plantations represent a vital economic sector in Indonesia. However, farmers who rely on plantations for their livelihood often encounter challenges related to air and soil quality, which can significantly impact plant growth. Each type of plant requires specific air and soil conditions to thrive optimally, including factors such as air temperature, humidity, soil moisture, and pH levels. To address these issues, a solution has been developed in the form of a plantation monitoring system that can be accessed remotely and in real-time through cellular and desktop applications. This monitoring s
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Bian, Mingbo, Zhichao Chen, Yiguang Fan, et al. "Integrating Spectral, Textural, and Morphological Data for Potato LAI Estimation from UAV Images." Agronomy 13, no. 12 (2023): 3070. http://dx.doi.org/10.3390/agronomy13123070.

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The Leaf Area Index (LAI) is a crucial indicator of crop photosynthetic potential, which is of great significance in farmland monitoring and precision management. This study aimed to predict potato plant LAI for potato plant growth monitoring, integrating spectral, textural, and morphological data through UAV images and machine learning. A new texture index named VITs was established by fusing multi-channel information. Vegetation growth features (Vis and plant height Hdsm) and texture features (TIs and VITs) were obtained from drone digital images. Various feature combinations (VIs, VIs + TIs
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Morris, Jesse R., Steven L. Petersen, Matthew D. Madsen, Brock R. McMillan, Dennis L. Eggett, and C. Russell Lawrence. "Monitoring Seedling Emergence, Growth, and Survival Using Repeat High-Resolution Imagery." Remote Sensing 14, no. 21 (2022): 5365. http://dx.doi.org/10.3390/rs14215365.

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Environmental factors often limit plant establishment and survival through increased seedling mortality. Understanding plant growth and the causes of mortality can be helpful in developing solutions that enhance seeding success and improve restoration monitoring. The purpose of our research was to assess the efficacy of time lapse and motion sensing cameras for monitoring seedling height, density, and fate. We conducted this study in a salt desert shrub community in northwest Utah, USA. In spring 2017, we placed 28 cameras in fenced and unfenced plots seeded with bottlebrush squirreltail and c
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Lo Presti, Daniela, Sara Cimini, Carlo Massaroni, et al. "Plant Wearable Sensors Based on FBG Technology for Growth and Microclimate Monitoring." Sensors 21, no. 19 (2021): 6327. http://dx.doi.org/10.3390/s21196327.

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Plants are primary resources for oxygen and foods whose production is fundamental for our life. However, diseases and pests may interfere with plant growth and cause a significant reduction of both the quality and quantity of agriculture products. Increasing agricultural productivity is crucial for poverty reduction and food security improvements. For this reason, the 2030 Agenda for Sustainable Development gives a central role to agriculture by promoting a strong technological innovation for advancing sustainable practices at the plant level. To accomplish this aim, recently, wearable sensors
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Smolders, Erik, Roel Merckx, Frans Schoovaerts, and Karel Vlassak. "Continuous shoot growth monitoring in hydroponics." Physiologia Plantarum 83, no. 1 (1991): 83–92. http://dx.doi.org/10.1111/j.1399-3054.1991.tb01285.x.

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Moysiadis, Vasileios, Georgios Kokkonis, Stamatia Bibi, Ioannis Moscholios, Nikolaos Maropoulos, and Panagiotis Sarigiannidis. "Monitoring Mushroom Growth with Machine Learning." Agriculture 13, no. 1 (2023): 223. http://dx.doi.org/10.3390/agriculture13010223.

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Mushrooms contain valuable nutrients, proteins, minerals, and vitamins, and it is suggested to include them in our diet. Many farmers grow mushrooms in restricted environments with specific atmospheric parameters in greenhouses. In addition, recent technologies of the Internet of things intend to give solutions in the agriculture area. In this paper, we evaluate the effectiveness of machine learning for mushroom growth monitoring for the genus Pleurotus. We use YOLOv5 to detect mushrooms’ growing stage and indicate those ready to harvest. The results show that it can detect mushrooms in the gr
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