IoT-based Yield Monitoring of Mulberry Silkworm Using Image Processing Technique

Aims: This project introduces a novel yield monitoring system for monitoring without physical interruption to track the details every single stage, designated as the “IOT based Yield Monitoring of Mulberry Silkworm using Image Processing Technique (IPT)”. Study Design: This system integrates three main components: Primary Camera Module with IOT Based Silkworm Monitoring system, Secondary Camera Module with Python Based Advanced Image Recognition process and IoT Based Smart Control System with Data Monitoring Systems. Each unit is intricately designed to perform specific tasks that contributes to overall functionary of the yield monitoring system. Methodology: The first unit, silkworm monitoring system, utilizes ESP32 Camera to control a OV2640 Camera module and 12volt DC power supply via relay module activated automatically full time. After the activation the camera tracks every change in the life cycle and yield and the data is convert to peripheral interface IC and webserver and also OLED display system. The second unit, the advance image recognition process, comprises python and advance ML based Optical Image recognition. This setup facilitates the connection of system user interface Tap UI/UX, Camera and CPU computer vision. This setup detects unhealthy silkworms and presence of diseases and pest related damage. The third and final unit, smart control system with data monitoring, employs a micro controller connected with temperature sensor, heating lamp, cooling fan, 12volt power supply, 12c module with LCD display and webserver. Results: This unit is designed to maintain the temperature and humidity. The sequence of operations ensures that yield monitoring of different stages without effecting the silkworm. This project automates to track the details anywhere in the world. Conclusion: This system promises efficiency to monitoring thermal conditions, silkworm lifecycle change in different stages, unhealthy silkworms and specifically, maximized yield.

Authors

Publication Details

Journal
Journal of Scientific Research and Reports
Published
2025-04-24
DOI
https://doi.org/10.9734/jsrr/2025/v31i53002
Primary Topic
Silkworms and Sericulture Research
Type
article
Field-Weighted Citation Impact
0.00
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article

IoT-based Yield Monitoring of Mulberry Silkworm Using Image Processing Technique

S. Mukesh Kumar, N. Vairam, D. Kishore, A. Sakthivel
Journal of Scientific Research and Reports
Silkworms and Sericulture Research
article

IoT-based Yield Monitoring of Mulberry Silkworm Using Image Processing Technique

S. Mukesh Kumar, N. Vairam, D. Kishore, A. Sakthivel
article en

Abstract

Aims: This project introduces a novel yield monitoring system for monitoring without physical interruption to track the details every single stage, designated as the “IOT based Yield Monitoring of Mulberry Silkworm using Image Processing Technique (IPT)”. Study Design: This system integrates three main components: Primary Camera Module with IOT Based Silkworm Monitoring system, Secondary Camera Module with Python Based Advanced Image Recognition process and IoT Based Smart Control System with Data Monitoring Systems. Each unit is intricately designed to perform specific tasks that contributes to overall functionary of the yield monitoring system. Methodology: The first unit, silkworm monitoring system, utilizes ESP32 Camera to control a OV2640 Camera module and 12volt DC power supply via relay module activated automatically full time. After the activation the camera tracks every change in the life cycle and yield and the data is convert to peripheral interface IC and webserver and also OLED display system. The second unit, the advance image recognition process, comprises python and advance ML based Optical Image recognition. This setup facilitates the connection of system user interface Tap UI/UX, Camera and CPU computer vision. This setup detects unhealthy silkworms and presence of diseases and pest related damage. The third and final unit, smart control system with data monitoring, employs a micro controller connected with temperature sensor, heating lamp, cooling fan, 12volt power supply, 12c module with LCD display and webserver. Results: This unit is designed to maintain the temperature and humidity. The sequence of operations ensures that yield monitoring of different stages without effecting the silkworm. This project automates to track the details anywhere in the world. Conclusion: This system promises efficiency to monitoring thermal conditions, silkworm lifecycle change in different stages, unhealthy silkworms and specifically, maximized yield.

Journal of Scientific Research and ReportsVol. 31(5)
Openalex Percentile: Top 92%
Silkworms and Sericulture Research
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IoT-based Yield Monitoring of Mulberry Silkworm Using Image Processing Technique — S. Mukesh Kumar, N. Vairam, et al. · Journal of Scientific Research and Reports (2025) | TGRS Research Map | TGRS