Deep Learning-Enabled Pest Detection System Using Sound Analytics in the Internet of Agricultural Things-Reference-Cited by-同舟云学术

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Deep Learning-Enabled Pest Detection System Using Sound Analytics in the Internet of Agricultural Things

Published:2023-11-15 Issue: Volume:2022 Page:123
ISSN:
Container-title:The 10th International Electronic Conference on Sensors and Applications
language:
Short-container-title:

Author:

Dhanaraj Rajesh Kumar¹,Ali Md. Akkas²³

Affiliation:

1. Symbiosis Institute of Computer Studies and Research, Symbiosis International (Deemed University), Pune 412115, India

2. School of Computing Science and Engineering, Galgotias University, Greater Noida 201310, India

3. Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/58/1/123/pdf

Reference12 articles.

1. Gupta, B., Madan, G., and Md, A.Q. (2022). A smart agriculture framework for IoT-based plant decay detection using innovative croft algorithm. Mater. Today Proc., 4758–4763.

2. Development of IoT-based smart agriculture monitoring system algorithms;Siddiquee;Wirel. Commun. Mob. Comput.,2022

3. Security in IoT-enabled smart agriculture: Architecture, security solutions, and challenges;Vangala;Clust. Comput.,2023

4. A Survey on LoRa for Smart Agriculture: Current Trends and Future Perspectives;Pagano;IEEE IoT J.,2022

5. IoT-equipped and AI-enabled next generation smart agriculture: A critical review, current challenges, and future trends;Qazi;IEEE Access,2022

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