Intelligent NB-IoT and Emotion-Aware Monitoring System for Proactive Wildlife Security.
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| Title: | Intelligent NB-IoT and Emotion-Aware Monitoring System for Proactive Wildlife Security. |
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| Authors: | Nithya, R.1 nithyaravicse@gmail.com, Peo Mariadas, A. Emmanuel2 emmanuelpeo@gmail.com, ANBARASU, Muthu Manickam2 muthumanicckam@gmail.com, RAVINDRAN, Sornalatha3 ravindransornalatha@gmail.com |
| Source: | Technical Gazette / Tehnički Vjesnik. 2026, Vol. 33 Issue 3, p1139-1147. 9p. |
| Subjects: | Wildlife monitoring, Emotion recognition, Artificial intelligence, Edge computing, Wildlife conservation, Adaptive natural resource management |
| Abstract: | Conventional wildlife protection systems primarily rely on fixed geofencing and basic GPS tracking, which are limited in their ability to capture the behavioral and emotional states of animals under threat. This paper proposes a smart, AI-powered monitoring framework that integrates emotion recognition and adaptive geofencing to enhance wildlife security. The system identifies early warning indicators of fear, distress, or pain by analyzing multimodal data such as animal movement, acoustic signals, and biometric readings. To complement this, edge computing is leveraged with NB-IoT-enabled ground robots that patrol forest areas, process data locally, and provide real-time behavioural explanations. These robots not only detect anomalous events but also interpret activities, offering meaningful context to conservation teams. A key feature of the framework is the use of Explainable AI, which ensures transparency by justifying alerts raised and enabling forest rangers to make rapid, informed decisions. Unlike traditional static boundaries, the proposed adaptive geofencing dynamically adjusts virtual barriers based on animal movement patterns, environmental risks, and time-specific factors. Furthermore, the system incorporates an intelligent energy-saving mechanism, reducing unnecessary data transmission and extending the lifespan of field-deployed devices. By combining emotional intelligence, robotic surveillance, and explainable decision-making, the proposed model advances wildlife conservation from reactive poacher detection to proactive animal-centric protection. This holistic approach enables not only the safeguarding of endangered species but also a deeper understanding of their behavioural responses, ultimately fostering smarter and more sustainable conservation practices. [ABSTRACT FROM AUTHOR] |
| Copyright of Technical Gazette / Tehnički Vjesnik is the property of Tehnicki Vjesnik and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 195131802 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Intelligent NB-IoT and Emotion-Aware Monitoring System for Proactive Wildlife Security. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Nithya%2C+R%2E%22">Nithya, R.</searchLink><relatesTo>1</relatesTo><i> nithyaravicse@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Peo+Mariadas%2C+A%2E+Emmanuel%22">Peo Mariadas, A. Emmanuel</searchLink><relatesTo>2</relatesTo><i> emmanuelpeo@gmail.com</i><br /><searchLink fieldCode="AR" term="%22ANBARASU%2C+Muthu+Manickam%22">ANBARASU, Muthu Manickam</searchLink><relatesTo>2</relatesTo><i> muthumanicckam@gmail.com</i><br /><searchLink fieldCode="AR" term="%22RAVINDRAN%2C+Sornalatha%22">RAVINDRAN, Sornalatha</searchLink><relatesTo>3</relatesTo><i> ravindransornalatha@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Technical+Gazette+%2F+Tehnički+Vjesnik%22">Technical Gazette / Tehnički Vjesnik</searchLink>. 2026, Vol. 33 Issue 3, p1139-1147. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Wildlife+monitoring%22">Wildlife monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Emotion+recognition%22">Emotion recognition</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Edge+computing%22">Edge computing</searchLink><br /><searchLink fieldCode="DE" term="%22Wildlife+conservation%22">Wildlife conservation</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+natural+resource+management%22">Adaptive natural resource management</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Conventional wildlife protection systems primarily rely on fixed geofencing and basic GPS tracking, which are limited in their ability to capture the behavioral and emotional states of animals under threat. This paper proposes a smart, AI-powered monitoring framework that integrates emotion recognition and adaptive geofencing to enhance wildlife security. The system identifies early warning indicators of fear, distress, or pain by analyzing multimodal data such as animal movement, acoustic signals, and biometric readings. To complement this, edge computing is leveraged with NB-IoT-enabled ground robots that patrol forest areas, process data locally, and provide real-time behavioural explanations. These robots not only detect anomalous events but also interpret activities, offering meaningful context to conservation teams. A key feature of the framework is the use of Explainable AI, which ensures transparency by justifying alerts raised and enabling forest rangers to make rapid, informed decisions. Unlike traditional static boundaries, the proposed adaptive geofencing dynamically adjusts virtual barriers based on animal movement patterns, environmental risks, and time-specific factors. Furthermore, the system incorporates an intelligent energy-saving mechanism, reducing unnecessary data transmission and extending the lifespan of field-deployed devices. By combining emotional intelligence, robotic surveillance, and explainable decision-making, the proposed model advances wildlife conservation from reactive poacher detection to proactive animal-centric protection. This holistic approach enables not only the safeguarding of endangered species but also a deeper understanding of their behavioural responses, ultimately fostering smarter and more sustainable conservation practices. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Technical Gazette / Tehnički Vjesnik is the property of Tehnicki Vjesnik and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.17559/TV-20250827002927 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 1139 Subjects: – SubjectFull: Wildlife monitoring Type: general – SubjectFull: Emotion recognition Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Edge computing Type: general – SubjectFull: Wildlife conservation Type: general – SubjectFull: Adaptive natural resource management Type: general Titles: – TitleFull: Intelligent NB-IoT and Emotion-Aware Monitoring System for Proactive Wildlife Security. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Nithya, R. – PersonEntity: Name: NameFull: Peo Mariadas, A. Emmanuel – PersonEntity: Name: NameFull: ANBARASU, Muthu Manickam – PersonEntity: Name: NameFull: RAVINDRAN, Sornalatha IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 13303651 Numbering: – Type: volume Value: 33 – Type: issue Value: 3 Titles: – TitleFull: Technical Gazette / Tehnički Vjesnik Type: main |
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