Efficient Air Quality Index Prediction on Resource-Constrained Devices using TinyML: Design, Implementation, and Evaluation-Reference-Cited by-同舟云学术

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Efficient Air Quality Index Prediction on Resource-Constrained Devices using TinyML: Design, Implementation, and Evaluation

Published:2024-01-04 Issue: Volume: Page:304-309
ISSN:
Container-title:Proceedings of the 25th International Conference on Distributed Computing and Networking
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Author:

Datta Arko¹^ORCID,Pal Aniruddha²^ORCID,Marandi Ranbir³^ORCID,Chattaraj Nilanjan³^ORCID,Nandi Subrata¹^ORCID,Saha Sujoy¹^ORCID

Affiliation:

1. Computer Science and Engineering, National Institute of Technology, Durgapur, India

2. Computer Science and Engineering, Bengal College of Engineering and Technology, India

3. Electronics and Communication Engineering, National Institute of Technology, Durgapur, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3631461.3631956

Reference7 articles.

1. A TinyML Soft-Sensor Approach for Low-Cost Detection and Monitoring of Vehicular Emissions

2. An Adaptable and Unsupervised TinyML Anomaly Detection System for Extreme Industrial Environments

3. AQuaMoHo : Localized Low-cost Outdoor Air Quality Sensing over a Thermo-hygrometer

4. A review on TinyML: State-of-the-art and prospects

5. Can I go for a roof walk today?

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