The morphological complexity of urban environments results in a high spatial and temporal variability of the urban microclimate. The consequent demand for highly-resolution atmospheric data remains a challenge for atmospheric research and operational application. The recent widespread availability and increasing adoption of low-cost mobile sensing offers the opportunity to integrate observations from conventional monitoring networks with microclimatic and air pollution data at a finer spatial and temporal scale. So far, the relatively low quality of the measurements and outdoor performance compared to conventional instrumentation has discouraged the full deployment of mobile sensors for routine monitoring. The present study addresses the performance of a commercial mobile sensor, the MeteoTracker (IoTopon Srl), recently launched on the market to quantify the microclimatic characteristics of the outdoor environment. The sensor follows the philosophy of the Internet of Things technology, being low cost, having an automatic data flow via personal smartphones and online data sharing, supporting user-friendly software, and having the potential to be deployed in large quantities. In this paper, the outdoor performance is evaluated through tests aimed at quantifying (i) the intra-sensor variability under similar atmospheric conditions and (ii) the outdoor accuracy compared to a reference weather station under sub-optimal (in fixed location) and optimal (mobile) sensor usage. Data-driven corrections are developed and successfully applied to improve the MeteoTracker data quality. In particular, a recursive method for the simultaneous improvement of relative humidity, dew point, and humidex index proves crucial for increasing the data quality. The results mark an intra-sensor variability in the range of +/-0.5 C for air temperature and +/-1.2 % for the corrected relative humidity, both within the declared sensor accuracy. The sensor captures the same atmospheric variability as the reference sensor during both fixed and mobile tests, showing positive biases (overestimation) for both variables. Through the mobile test, the outdoor accuracy is observed between +/-0.3 C to +/-0.5 C for air temperature, between +/-3 % and +/-5 % for the relative humidity, ranking the MeteoTracker in the real accuracy range of similar commercial sensors from the literature and making it a valid solution for atmospheric monitoring.

Performance Evaluation of MeteoTracker Mobile Sensor for Outdoor Applications / Barbano, Francesco; Brattich, Erika; Cintolesi, Carlo; Nizamani, Abdul Ghafoor; Di Sabatino, Silvana; Milelli, Massimo; Peerlings, Esther E. M.; Polder, Sjoerd; Steeneveld, Gert-Jan; Parodi, Antonio. - In: ATMOSPHERIC MEASUREMENT TECHNIQUES. - ISSN 1867-8548. - ELETTRONICO. - 17:10(2024), pp. 3255-3278. [10.5194/amt-17-3255-2024]

Performance Evaluation of MeteoTracker Mobile Sensor for Outdoor Applications

Barbano, Francesco
Primo
;
Brattich, Erika;Cintolesi, Carlo;Nizamani, Abdul Ghafoor;Di Sabatino, Silvana;
2024

Abstract

The morphological complexity of urban environments results in a high spatial and temporal variability of the urban microclimate. The consequent demand for highly-resolution atmospheric data remains a challenge for atmospheric research and operational application. The recent widespread availability and increasing adoption of low-cost mobile sensing offers the opportunity to integrate observations from conventional monitoring networks with microclimatic and air pollution data at a finer spatial and temporal scale. So far, the relatively low quality of the measurements and outdoor performance compared to conventional instrumentation has discouraged the full deployment of mobile sensors for routine monitoring. The present study addresses the performance of a commercial mobile sensor, the MeteoTracker (IoTopon Srl), recently launched on the market to quantify the microclimatic characteristics of the outdoor environment. The sensor follows the philosophy of the Internet of Things technology, being low cost, having an automatic data flow via personal smartphones and online data sharing, supporting user-friendly software, and having the potential to be deployed in large quantities. In this paper, the outdoor performance is evaluated through tests aimed at quantifying (i) the intra-sensor variability under similar atmospheric conditions and (ii) the outdoor accuracy compared to a reference weather station under sub-optimal (in fixed location) and optimal (mobile) sensor usage. Data-driven corrections are developed and successfully applied to improve the MeteoTracker data quality. In particular, a recursive method for the simultaneous improvement of relative humidity, dew point, and humidex index proves crucial for increasing the data quality. The results mark an intra-sensor variability in the range of +/-0.5 C for air temperature and +/-1.2 % for the corrected relative humidity, both within the declared sensor accuracy. The sensor captures the same atmospheric variability as the reference sensor during both fixed and mobile tests, showing positive biases (overestimation) for both variables. Through the mobile test, the outdoor accuracy is observed between +/-0.3 C to +/-0.5 C for air temperature, between +/-3 % and +/-5 % for the relative humidity, ranking the MeteoTracker in the real accuracy range of similar commercial sensors from the literature and making it a valid solution for atmospheric monitoring.
2024
Performance Evaluation of MeteoTracker Mobile Sensor for Outdoor Applications / Barbano, Francesco; Brattich, Erika; Cintolesi, Carlo; Nizamani, Abdul Ghafoor; Di Sabatino, Silvana; Milelli, Massimo; Peerlings, Esther E. M.; Polder, Sjoerd; Steeneveld, Gert-Jan; Parodi, Antonio. - In: ATMOSPHERIC MEASUREMENT TECHNIQUES. - ISSN 1867-8548. - ELETTRONICO. - 17:10(2024), pp. 3255-3278. [10.5194/amt-17-3255-2024]
Barbano, Francesco; Brattich, Erika; Cintolesi, Carlo; Nizamani, Abdul Ghafoor; Di Sabatino, Silvana; Milelli, Massimo; Peerlings, Esther E. M.; Polder, Sjoerd; Steeneveld, Gert-Jan; Parodi, Antonio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/962321
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