Internet of Things-Based Crop Classification Model Using Deep Learning for Indirect Solar Drying

The energy which is obtained from the sun in the form of light and heat is known as solar energy. Nowadays, technology is focused on utilization of this rich resource of energy. So many ways to harness and utilize this source of energy have already been introduced; solar drying of crops is one of its applications. Drying of crops is required to improve the quality of the crops as well as to protect crops from so many unwanted issues like moisture, pest/insect attacks, and birds/animals. Traditional methods are still used to dry the crops; drying of crops is required to preserving food product for long time. In this paper, we studied about the working mechanism of indirect solar dryers and introduced IoT-based system to control and monitor the temperature of the solar dryer as per the requirement of specific crop. To achieve the automation accurately and precisely deep learning method is also used to set the required temperature according to the requirement of the specific crop.

[1]  S. Rayhan Kabir,et al.  Evolution of Industry and Blockchain Era: Monitoring Price Hike and Corruption Using BIoT for Smart Government and Industry 4.0 , 2022, IEEE Transactions on Industrial Informatics.

[2]  Pradeep Kumar Singh,et al.  An intelligent WSN-UAV-based IoT framework for precision agriculture application , 2022, Comput. Electr. Eng..

[3]  R. Priyadarshini,et al.  Intelligent Semantic Segmentation for Self-Driving Vehicles Using Deep Learning , 2022, Comput. Intell. Neurosci..

[4]  S. Kautish,et al.  Cloud-Based Fault Prediction Using IoT in Office Automation for Improvisation of Health of Employees , 2021, Journal of healthcare engineering.

[5]  A. Salehi,et al.  COVID-19: Automated Detection and Monitoring of Patients Worldwide Using Machine Learning , 2021, Modeling, Control and Drug Development for COVID-19 Outbreak Prevention.

[6]  Thippa Reddy Gadekallu,et al.  Blockchain-Based Reliable and Efficient Certificateless Signature for IIoT Devices , 2021, IEEE Transactions on Industrial Informatics.

[7]  Wei Yu,et al.  Application of CAD in Product Packaging Design Based on Green Concept , 2021 .

[8]  Ram Prakash Dwivedi,et al.  Arduino based LPG Leakage Detection and Prevention System , 2021, 2021 8th International Conference on Computing for Sustainable Global Development (INDIACom).

[9]  Brij Bhushan Sharma,et al.  IoT-Based Intelligent Irrigation System for Paddy Crop Using an Internet-Controlled Water Pump , 2021, Int. J. Agric. Environ. Inf. Syst..

[10]  A. Hassanien,et al.  Sentiment Analysis of COVID-19 tweets by Deep Learning Classifiers—A study to show how popularity is affecting accuracy in social media , 2020, Applied Soft Computing.

[11]  Gaurav Gupta,et al.  A CNN Model: Earlier Diagnosis and Classification of Alzheimer Disease using MRI , 2020, 2020 International Conference on Smart Electronics and Communication (ICOSEC).

[12]  López-Vidaña Erick César,et al.  Thermal performance of a passive, mixed-type solar dryer for tomato slices (Solanum lycopersicum) , 2020 .

[13]  D. Maier,et al.  CFD simulation of corn drying in a natural convection solar dryer , 2018 .

[14]  V. P. Chandramohan,et al.  Design, Development and Performance of Indirect Type Solar Dryer for Banana Drying ☆ , 2017 .

[15]  Maundu Nicholas Musembi,et al.  Design and Analysis of Solar Dryer for Mid-Latitude Region , 2016 .

[16]  V. Hegde,et al.  Design, fabrication and performance evaluation of solar dryer for banana , 2015 .

[17]  Mohsen Guizani,et al.  Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications , 2015, IEEE Communications Surveys & Tutorials.

[18]  S. Maiti,et al.  Performance evaluation of a small scale indirect solar dryer with static reflectors during non-summer months in the Saurashtra region of western India , 2011 .

[19]  Panna Lal Singh.  Silk cocoon drying in forced convection type solar dryer , 2011 .

[20]  J. Havlík,et al.  Design and performance evaluation of a Double-pass solar drier for drying of red chilli (Capsicum annum L.) , 2011 .

[21]  Abdul Jabbar N. Khalifa,et al.  Testing of the performance of a fruit and vegetable solar drying system in Iraq , 2007 .

[22]  G. N. Tiwari,et al.  Effect of mass on convective mass transfer coefficient during open sun and greenhouse drying of onion flakes , 2007 .

[23]  G. N. Tiwari,et al.  Performance of a reverse flat plate absorber cabinet dryer: a new concept , 1999 .

[24]  Arwa A. Mashat,et al.  Proportional Fairness Based Energy Efficient Routing in Wireless Sensor Network , 2022, Computer Systems Science and Engineering.

[25]  Keping Yu,et al.  Secure routing for LEO satellite network survivability , 2022, Comput. Networks.

[26]  Sudhakar Sengan,et al.  Improved Energy Based Multi-Sensor Object Detection in Wireless Sensor Networks , 2022, Intelligent Automation & Soft Computing.

[27]  Aaditya Sharma,et al.  An IoT-Based Soil Properties Monitoring System for Crop Growth and Production , 2021 .

[28]  Nagesh Kumar,et al.  Applicability Of Wireless Sensor Networks & Iot In Saffron & Wheat Crops: A Smart Agriculture Perspective , 2020 .

[29]  Nagesh Kumar,et al.  Internet of Things-Based Hardware and Software for Smart Agriculture: A Review , 2019 .

[30]  K. Sopian,et al.  Performance analysis of solar drying system for red chili , 2014 .

[31]  Varun,et al.  Construction and Performance Analysis of an Indirect Solar Dryer Integrated with Solar Air Heater , 2012 .

[32]  R. L. Sawhney,et al.  Review of research and development work on solar dryers for grape drying , 2002 .