Integrating IoT and Machine Learning for Efficient Pest Management in Greenhouses

Please use this identifier to cite or link to this item: http://archive.cmb.ac.lk:8080/xmlui/handle/70130/7475

Full metadata record

DC Field	Value	Language
dc.contributor.author	Nirmala, M.S.	-
dc.date.accessioned	2024-12-12T06:06:50Z	-
dc.date.available	2024-12-12T06:06:50Z	-
dc.date.issued	2024	-
dc.identifier.citation	Thesis - Master of Computer Science	en_US
dc.identifier.uri	http://archive.cmb.ac.lk:8080/xmlui/handle/70130/7475	-
dc.description.abstract	This thesis proposes a novel design for a pest management system that increases agricultural productivity by integrating Internet of Things (IoT) technologies and Machine Learning (ML) ...	en_US
dc.language.iso	en_US	en_US
dc.subject	IoT (Internet of Things)	en_US
dc.subject	Machine Learning	en_US
dc.subject	Pest Management	en_US
dc.subject	Greenhouses	en_US
dc.subject	Precision Agriculture	en_US
dc.subject	Smart Farming	en_US
dc.subject	Sensor Networks	en_US
dc.subject	Data-Driven Decision Making	en_US
dc.subject	Crop Protection	en_US
dc.subject	Real-Time Monitoring	en_US
dc.subject	Environmental Sensors	en_US
dc.subject	Predictive Analytics	en_US
dc.subject	Automated Pest Detection	en_US
dc.subject	Sustainable Agriculture	en_US
dc.subject	Smart Greenhouse Systems	en_US
dc.subject	Integrated Pest Management (IPM)	en_US
dc.subject	Climate Control Systems	en_US
dc.subject	Energy-Efficient Pest Control	en_US
dc.subject	Agricultural IoT Devices	en_US
dc.subject	Computer Vision for Pest Detection	en_US
dc.title	Integrating IoT and Machine Learning for Efficient Pest Management in Greenhouses	en_US
dc.type	Thesis	en_US
Appears in Collections:	Masters Theses - University of Colombo School of Computing

Files in This Item:

File	Description	Size	Format
UCSC - Master Theses.pdf		1.23 MB	Adobe PDF	View/Open