Automated Gardening (Part 2)

More recent developments include cooling systems which use either cold water or aglycone, through heat exchanges, to both lower the temperature and lower the humidity. Because once the air is called below the dew point the water, lets you drop out of the air and allows you to control humidity in very high areas. In terms of the User interfacing of the control systems, the controller is done by the controller and the controller works in bits and bytes. The users generally don’t understand bits and bytes and systems are made useable for the users. To do this a user interface is needed and it includes a PC with text-based settings and readouts by texts, but they also include a graphic user interface. There have been apps developed nowadays at Priva, they have an app that allows remotely to connect to greenhouses globally to monitor and control. With any application, Data collection is collected continually from the time it is installed and users do look at data daily to see what they should do with their settings and their crop. Managers or farmers on the other hand will look at their data and make decisions as to when they should be harvesting and how much they should be harvesting.

The amount of people that have indeed been influenced into gardening due to the lockdown has for sure increased. Mainly because gardening activities have a positive impact on mental health (Panno,2021). This is evident from the motivation of this project even, as I had seen gardening as an escape; as well as many of my friends and family also. Lockdown keeping people inside was always going to affect day-to-day lives. Panno investigation led me to further understand the extent to which everyone’s activities have improved; environmentally speaking. In terms of pollution in our environments, plants and trees are accommodating in terms of mitigation. They play an important role in the ecosystem. Catering to our needs such as food, medicinal purposes, fiber, fuel, and timber. Oxygen and carbon dioxide in the atmosphere are sourced by trees and plants. Noise pollution for instance is prevented by trees such as Ashok, Tamarind & Neem. In terms of medicinal purposes, there is a selection of herbs that effectively help the human body and are common medicinal solutions for many globally. There are various technological procedures to detect the effectiveness of herbs, one that caught my attention due to investigation; is Raman spectroscopy. This procedure is well known for the analysis of herbs and various other materials. Its usage allows the inspection of microanalysis, allowing readable data that is naked to the human eye.

Automated systems aid the discovery of various diseases in plants. Before technological advances, many farmers were using their naked eye, which for sure was more complicated and costly as crops or produce may be expensive. Because the main part of a plant is its leaves, the life cycle of a plant is affected significantly once the leaves have caught any disease. Therefore, a solution of machine learning is more than capable to resolve this dilemma. From the use of machine learning, investigations of digital image processing by Jun Liu & Xuewei Wang evidence the effectiveness of disease detection in plants through machine learning (Liu & Wang, 2021). From the use of detection methods many agricultural invested individuals benefit from software that can fasten their process to examine their produce and crops. As well as this the investigations of Jun Liu & Xuewei Wang noted that the use of a convolutional neural network is also a benefit. As It has various layers that lead up to detecting the specified subject. The layers start from layer, convolution layer, pooling layer, convolution layer, pooling layer, full connection layer & SoftMax. The study, also expresses that companies have not only gained research value but also a market idea prospect. This section on disease detection and well fare of plants & crops further expresses the effectiveness of automated systems in agriculture.

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References

Theodorou, A., Panno, A., Carrus, G., Carbone, G.A., Massullo, C. and Imperatori, C., 2021. Stay home, stay safe, stay green: The role of gardening activities on mental health during the Covid-19 home confinement. Urban Forestry & Urban Greening, 61, p.127091. Deepa, R. N and C. Shetty, "A Machine Learning Technique for Identification of Plant Diseases in Leaves," 2021 6th International Conference on Inventive Computation Technologies (ICICT), 2021, pp. 481-484, doi: 10.1109/ICICT50816.2021.9358797. Liu, J. and Wang, X. (2021). Plant diseases and pests detection based on deep learning: a review. Plant Methods, 17(1). Wired. (n.d.). A Solar-Powered Soil Sensor for Serious Gardeners. [online] Available at: https://www.wired.com/2015/04/edyn-garden-sensor/ [Accessed 29 Apr. 2021]. The Temboo Blog. (2020). Soil Moisture: More Important Than You Think. [online] Available at: https://blog.temboo.com/soil-moisture/. IOT Solutions World Congress | DIGITALIZING INDUSTRIES. (2019). IOT TRANSFORMING THE FUTURE OF AGRICULTURE | IOT Solutions World Congress | DIGITALIZING INDUSTRIES. [online] Available at: https://www.iotsworldcongress.com/iot-transforming-the-future-of-agriculture/.