Monitoring of Hydroponics Plant and Prediction of Leaf Disease using IOT

Deepika, V.; Kalaiselvi, A.; Dhivyaarthi, G

doi:10.1109/icaeca52838.2021.9675651

Cited by 5 publications

(1 citation statement)

References 9 publications

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“…Large diameter pipe Water pump [27] using IoT which consists of a NodeMCU microcontroller, DHT22, 3 in-1 analog Ph meter, and water level indicator, comparator module, 4 channel relay, 2 motors, and smartphones.…”

Section: Small Diameter Pipe Pipe Capmentioning

confidence: 99%

Use of Tower System in Vertical Farming Technique

Putri,

Oktavionry,

Arlius

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Vertical agriculture in urban areas is a new phenomenon where interest is needed in order to develop. The objective of the research is to develop the tower system in vertical farming technique. In this research, tower could produce 624 plants. This tower is made using PVC pipe with 26 holes per tower. Each set of towers is equipped with an irrigation system, namely a water pump to drain nutrient water in the pipe. The way this monitoring system works is that the ESP 32 Series is connected to a voltage source so that it will be integrated to turn on and the system will check the ESP 32 Series connection with the internet. Sensors will be active and read data, when the DHT22 sensor detects a temperature of 33° then the fan will turn on, also if humidity <60% then the misting will turn on. The monitoring system works well. Data from temperature and humidity readings can be controlled and known. The average plant height of Bok choy is 8.89 cm, leaf width is 7.40 cm, leaf length is 10.33 cm, and the number of leaves is 10.24 strands. So, this system recommended to increasing the production in urban area.

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Section: Small Diameter Pipe Pipe Capmentioning

confidence: 99%

Use of Tower System in Vertical Farming Technique

Putri,

Oktavionry,

Arlius

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Digital Agriculture: Harnessing IoT and Data Analytics for Smart Farming Solutions

Ravichandran,

Dhanabalan,

Santhanakrishnan

et al. 2024

E3S Web of Conf.

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The integration of convolutional neural networks (CNN) and the Internet of Things (IoT) is an increasingly popular subject among scholars due to its potential to revolutionize the agricultural sector. The IoT will decrease resource wastage by enabling farmers to utilize sensor node data for decision-making instead of just depending on expertise. (e.g., fertilizers, water, pesticides, and fumigants). CNN enhances monitoring systems by predicting the amount of consumable resources needed to improve productivity and detect agricultural illnesses early. SAgric-IoT is a technological platform created for precision agriculture. It combines CNN and IoT to monitor physical and environmental factors, identify illnesses at an early stage, and manage greenhouse irrigation and fertilization. The findings indicate that SAgric-IoT is a dependable Internet of Things (IoT) platform characterized by minimal packet loss, significant energy conservation, and disease detection and classification processes exceeding 90% accurate.

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