Plantosphere: Next Generation Adaptive and Smart Agriculture System

Author:

Verma Abhishek1,Agrawal Manas1,Gupta Kartik1,Jamshed Aatif1,Mishra Anurag1,Khatter Harsh2ORCID,Gupta Gopal3,Neupane Sanjeev Chandra4ORCID

Affiliation:

1. ABES Engineering College, Ghaziabad, Uttar Pradesh, India

2. KIET Group of Institutions, Delhi NCR, Ghaziabad, Uttar Pradesh, India

3. ABESIT College of Engineering, Ghaziabad, India

4. AV Digitals, Pulchowk, Lalitpur, Nepal

Abstract

Around 75% of the population in India is engaged in agriculture and farming. The sustainability of every economy is based on agriculture. It has a major influence on financial growth and fundamental transformation in the long run. Artificial intelligence will usher in a revolution in agricultural operations in the future. This revolution has protected crops from being negatively affected by a variety of factors such as climate change, soil porosity, and water availability. Crop monitoring, soil management, and insect identification, to name a few examples, are all conceivable uses of artificial intelligence in agriculture. The primary purpose of artificial intelligence is to close the knowledge gap that exists between inventors and farmers. Detecting disease and monitoring plant health are two of the most difficult challenges in sustainable farming. As a result, image processing technology must be used to detect plant sickness at an early stage. Photographic capture, preprocessing, segmentation, feature extraction, and sickness categorization are all part of the procedure. In reality, computer image processing was used long before human eyes were able to detect the signs and symptoms of the disease. Taking into account the climatic conditions in various parts of the world. Climate change directly affects crop output. Several soil and atmospheric characteristics are detected to anticipate the optimal crop. Sedimentation is measured by soil parameters such as pH and moisture. Today, a platform that allows farmers to advertise their products is in high demand. This paper proposes a system where farmers sell directly to clients, bypassing wholesalers and traders. A predictive analytics solution is required to maximize the farmer’s profit.

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Instrumentation,Control and Systems Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Internet-of-Things-Enabled Sensor Networks: Vision Challenges and Smart Applications;Advances in Computing Communications and Informatics;2024-02-28

2. Potato Leaf Disease Classification Using Deep Learning Model;Communications in Computer and Information Science;2024

3. Retracted: Plantosphere: Next Generation Adaptive and Smart Agriculture System;Journal of Sensors;2023-08-23

4. Plant Leaf Diseases Severity Estimation using Fine-Tuned CNN Models;2023 6th International Conference on Information Systems and Computer Networks (ISCON);2023-03-03

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