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Tech-Driven Forest Conservation: Combating Deforestation With Internet of Things, Artificial Intelligence, and Remote Sensing

  • Bushra Haq
  • , Muhammad Ali Jamshed
  • , Senior Member
  • , Kamran Ali
  • , Bakhtiar Kasi
  • , Saira Arshad
  • , Mumraiz Khan Kasi
  • , Imran Ali
  • , Aqsa Shabbir
  • , Qammer H. Abbasi
  • , Masood Ur-Rehman
  • Balochistan University of Information Technology, Engineering and Management Sciences
  • University of Glasgow
  • Middlesex University
  • Lahore College for Women University, Lahore

Research output: Contribution to journalArticlepeer-review

70 Scopus citations

Abstract

—Deforestation poses a significant global environmental challenge with far-reaching consequences for biodiversity, climate change, and livelihoods. In this context, applying advanced technologies, such as the Internet of Things (IoT) and artificial intelligence (AI), holds immense promise. This article aims to comprehensively review and analyze the role of IoT, AI, and remote sensing technologies in monitoring, detecting, predicting, and preventing deforestation. By providing real-time data and enabling early detection, these technologies contribute to addressing activities like illegal logging, plant diseases, and forest fires. This review presents an overview of the advantages and limitations of these technologies, accompanied by an analysis of their current state and future potential. Key technologies covered include IoT, satellite imagery, drones, and AI algorithms, with each offering unique applications. Importantly, this article underscores the significance of these technologies in protecting forests and the diverse species they support. The findings discussed herein aim to inform ongoing debates and provide a foundation for further research in this crucial domain. Ultimately, the knowledge gained from this research has the potential to guide practical interventions and policies for effective forest conservation.

Original languageEnglish
Pages (from-to)24551-24568
Number of pages18
JournalIEEE Internet of Things Journal
Volume11
Issue number14
DOIs
StatePublished - 2024
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action
  2. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • Artificial intelligence (AI)
  • Internet of Things (IoT)
  • deep learning (DL)
  • deforestation
  • image processing
  • machine learning (ML)
  • remote sensing
  • wireless sensor networks (WSNs)

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