AI-IoT integrated framework for tree tilt monitoring: A case study on tree failure in Hong Kong

Chau, Wai Yi; Wang, Yu-Hsing; Chiu, Siu Wai; Tan, Pin Siang; Leung, Mei Ling; Lui, Hoi Lun; Wu, Jimmy; Lau, Yun Man

doi:10.1016/j.agrformet.2023.109678

Cited by 6 publications

(1 citation statement)

References 41 publications

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“…These sensors provide scalable, remote, and reasonably priced data collecting capabilities. As a result, there has been a significant change in favor of using IoT sensors to measure urban air quality in recent years [18]- [22].…”

Section: Review Of Literature 1 Using Iot Sensors To Monitor Urban Ai...mentioning

confidence: 99%

Performance Evaluation of IoT Sensors in Urban Air Quality Monitoring: Insights from the IoT Sensor Performance Test

Blinova,

Singh Chauhan,

Singla

et al. 2024

BIO Web Conf.

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In this paper, we report on extensive experiments conducted to evaluate Internet of Things (IoT) sensor performance in monitoring urban air quality. As certified sensors showed a considerably reduced air quality measurement error of 4.3% compared to uncalibrated sensors at 8.5%, our results highlight the crucial function of sensor calibration. The performance of sensors was impacted by environmental factors; higher temperatures produced better accuracy (3.6%), while high humidity levels caused sensors to react more quickly (2.3 seconds). The average air quality index (AQI) recorded by inside sensors was 45, but outside sensors reported an AQI of 60. This indicates that the positioning of the sensors had a substantial influence on the air quality data. Additionally, the methods of data transmission were examined, and it was found that Wi-Fi-transmitting sensors had lower latency (0.6 seconds) and data loss (1.8%) than cellular-transmitting sensors. These results emphasize the significance of environmental factors, sensor placement strategy, sensor calibration, and suitable data transmission techniques in maximizing IoT sensor performance for urban air quality monitoring, ultimately leading to more accurate and dependable air quality assessment.

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Section: Review Of Literature 1 Using Iot Sensors To Monitor Urban Ai...mentioning

confidence: 99%

Performance Evaluation of IoT Sensors in Urban Air Quality Monitoring: Insights from the IoT Sensor Performance Test

Blinova,

Singh Chauhan,

Singla

et al. 2024

BIO Web Conf.

View full text Add to dashboard Cite

show abstract

Harnessing Artificial Intelligence for Sustainable Bioenergy: Revolutionizing Optimization, Waste Reduction, and Environmental Sustainability

Anbarasu,

Thanigaivel,

Sathishkumar

et al. 2025

Bioresource Technology

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Towards automatic urban tree inventory: Enhancing tree instance segmentation via moving object removal and a chord length-based DBH estimation approach

Chau,

Chow,

Tan

et al. 2024

Computers and Electronics in Agriculture

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AI-IoT integrated framework for tree tilt monitoring: A case study on tree failure in Hong Kong

Cited by 6 publications

References 41 publications

Performance Evaluation of IoT Sensors in Urban Air Quality Monitoring: Insights from the IoT Sensor Performance Test

Performance Evaluation of IoT Sensors in Urban Air Quality Monitoring: Insights from the IoT Sensor Performance Test

Harnessing Artificial Intelligence for Sustainable Bioenergy: Revolutionizing Optimization, Waste Reduction, and Environmental Sustainability

Towards automatic urban tree inventory: Enhancing tree instance segmentation via moving object removal and a chord length-based DBH estimation approach

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