Embedded System-Based Sticky Paper Trap with Deep Learning-Based Insect-Counting Algorithm

Embedded System-Based Sticky Paper Trap with Deep Learning-Based Insect-Counting Algorithm

Flying insect detection, identification, and counting are the key components of agricultural pest management. Insect identification is also one of the most challenging tasks in agricultural image processing. With the aid of machine vision and machine learning, traditional (manual) identification and...

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Bibliographic Details
Main Author: József Sütő
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Electronics
Subjects:
deep learning
embedded system
insect pest counting
sticky paper trap
Online Access:https://www.mdpi.com/2079-9292/10/15/1754
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spelling doaj-4bfc32f601e44f6ea72119d9d48767932021-08-06T15:21:01ZengMDPI AGElectronics2079-92922021-07-01101754175410.3390/electronics10151754Embedded System-Based Sticky Paper Trap with Deep Learning-Based Insect-Counting AlgorithmJózsef Sütő0Department of IT Systems and Networks, University of Debrecen, 4032 Debrecen, HungaryFlying insect detection, identification, and counting are the key components of agricultural pest management. Insect identification is also one of the most challenging tasks in agricultural image processing. With the aid of machine vision and machine learning, traditional (manual) identification and counting can be automated. To achieve this goal, a particular data acquisition device and an accurate insect recognition algorithm (model) is necessary. In this work, we propose a new embedded system-based insect trap with an OpenMV Cam H7 microcontroller board, which can be used anywhere in the field without any restrictions (AC power supply, WIFI coverage, human interaction, etc.). In addition, we also propose a deep learning-based insect-counting method where we offer solutions for problems such as the “lack of data” and “false insect detection”. By means of the proposed trap and insect-counting method, spraying (pest swarming) could then be accurately scheduled.https://www.mdpi.com/2079-9292/10/15/1754deep learningembedded systeminsect pest countingsticky paper trap
collection DOAJ
language English
format Article
sources DOAJ
author József Sütő
spellingShingle József Sütő
Embedded System-Based Sticky Paper Trap with Deep Learning-Based Insect-Counting Algorithm
Electronics
deep learning
embedded system
insect pest counting
sticky paper trap
author_facet József Sütő
author_sort József Sütő
title Embedded System-Based Sticky Paper Trap with Deep Learning-Based Insect-Counting Algorithm
title_short Embedded System-Based Sticky Paper Trap with Deep Learning-Based Insect-Counting Algorithm
title_full Embedded System-Based Sticky Paper Trap with Deep Learning-Based Insect-Counting Algorithm
title_fullStr Embedded System-Based Sticky Paper Trap with Deep Learning-Based Insect-Counting Algorithm
title_full_unstemmed Embedded System-Based Sticky Paper Trap with Deep Learning-Based Insect-Counting Algorithm
title_sort embedded system-based sticky paper trap with deep learning-based insect-counting algorithm
publisher MDPI AG
series Electronics
issn 2079-9292
publishDate 2021-07-01
description Flying insect detection, identification, and counting are the key components of agricultural pest management. Insect identification is also one of the most challenging tasks in agricultural image processing. With the aid of machine vision and machine learning, traditional (manual) identification and counting can be automated. To achieve this goal, a particular data acquisition device and an accurate insect recognition algorithm (model) is necessary. In this work, we propose a new embedded system-based insect trap with an OpenMV Cam H7 microcontroller board, which can be used anywhere in the field without any restrictions (AC power supply, WIFI coverage, human interaction, etc.). In addition, we also propose a deep learning-based insect-counting method where we offer solutions for problems such as the “lack of data” and “false insect detection”. By means of the proposed trap and insect-counting method, spraying (pest swarming) could then be accurately scheduled.
topic deep learning
embedded system
insect pest counting
sticky paper trap
url https://www.mdpi.com/2079-9292/10/15/1754
work_keys_str_mv AT jozsefsuto embeddedsystembasedstickypapertrapwithdeeplearningbasedinsectcountingalgorithm
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