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Dataset of temperature and relative humidity measurements in domestic refrigerators in Bangkok Thailand
(2026-08-01)
Paviet-Salomon, Yvanne
;
Chaomuang, Nattawut
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Potisuwan, Cheeraphat
;
Derens-Bertheau, Evelyne
;
Nukunudompanich, Methawee
This dataset provides detailed measurements of internal air temperature, product temperature, and relative humidity in domestic refrigerators in households in Bangkok, Thailand. Data were collected from 123 households using Freshliance TagPlus-TH data loggers installed both inside and outside the refrigerators. For each refrigerator, air temperature and relative humidity were monitored at five internal locations: top shelf, middle shelf, vegetable drawer, door shelf, and freezer compartment. In addition, the temperature of a meat-like test product placed on the middle shelf was recorded. Ambient air conditions surrounding each refrigerator were also measured to characterize the external thermal environment. Prior to deployment, all sensors were prepared and activated by the research team, with time zero (T0) defined at this stage. Participants were only required to place the sensors according to the provided instructions while minimizing disturbances to their usual refrigerator usage habits. The sensors remained inside the refrigerators for seven consecutive days, recording measurements every 5 minutes before being removed. Data collected during the first and seventh days of monitoring were excluded from the analysis to account for the uncertainty regarding the exact times at which consumers placed and removed the sensors. This exclusion also helped eliminate transient effects caused by the introduction of heat loads during sensor installation and removal, which are not representative of normal refrigerator operating conditions. Consequently, only the five-day dataset corresponding to stabilized operating conditions is presented. The dataset is provided as tab-delimited.txt files. File names identify both the refrigerator number (1–123) and refrigerator configuration, including single-door, two-door top-freezer, and two-door bottom-freezer models. An accompanying R script enables the generation of temperature and humidity profiles for each refrigerator over the 5-day monitoring period. A README document is also included and provides detailed descriptions of column names, sensor locations, and metadata associated with each measurement campaign. Temperature sensors have a resolution of 0.1°C over a range of −30°C to +70°C, and an expanded uncertainty of ±0.5°C (k = 2). Relative humidity sensors have a resolution of 0.1 % and an expanded uncertainty of ±3 % (k = 2). These uncertainty values are based on the manufacturer’s specifications, additional calibration could not be performed within the scope of this study due to the lack of suitable calibration equipment. This high-resolution dataset provides valuable insights into the thermal and hygrometric conditions of domestic refrigeration systems under real household usage conditions. The data may support a wide range of applications, including the assessment and optimization of refrigeration performance through analysis of temperature heterogeneity and thermal behavior inside refrigerating compartments, the evaluation of food safety and risks associated with domestic storage temperatures, the identification of potential temperature abuse conditions in challenge-test studies, the development of consumer recommendations, the development and validation of simplified thermal models and CFD simulations for predicting airflow and heat transfer within domestic refrigerators, studies related to energy consumption and food preservation, and the optimization of domestic refrigerator design parameters using CFD and artificial neural network approaches. The dataset is expected to provide valuable insights for researchers, stakeholders, and policymakers working on refrigeration technologies, food safety, and cold-chain management.
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Dataset of air cargo supply chain conditions and fruit quality evolution: Case study of mango shipment from Thailand to France
(2025-08-01)
Paviet-Salomon, Y.
;
Laguerre, O.
;
Duret, S.
;
Denis, A.
;
Mawilai, P.
This study presents a detailed dataset collected during the international transport of mangoes (Mangifera indica L. cv. ‘Nam Dok Mai Si-Thong’) within a fully loaded Unit Load Device (ULD). The ULD contained 148 boxes (14 mangoes/box) and 31 boxes were instrumented by data loggers to monitor air and mango temperatures, as well as air humidity along the shipment. Measurements were recorded every 5 min throughout the 86.2 hour journey from Bangkok (Thailand) to Paris (France), it included cold storage, refrigerated transport, airport warehouse, air transport, and final delivery to the FRISE-INRAE laboratory in Paris suburban. At reception (Day 3), all boxes were stored at two temperatures (16 °C and 21 °C) over 15 days during which mango quality was assessed. Key quality attributes such as mass loss, peel color, pH, sugar content, and visual appearance were evaluated at Day 3, Day 6, Day 9, and Day 15 to highlight the impact of storage conditions on fruit quality. It is to be noticed that the same quality assessment was undertaken after harvest and before the cold storage in Thailand (Day 0). The dataset comprises raw and processed data files that include the temperature and humidity changes over time, as well as the quality evolution. These data are stored in series of txt files, with raw values and processed results i.e. min, max, average values, standard deviation and variance to facilitate future analysis. Additionally, the dataset includes series of jpeg files of mango images at different assessment days. This dataset is valuable for both practical and research purposes. For fruit exporters, it offers the insights into how different positions within a ULD can affect mango quality during a long-distance transport and implements certain measures to minimize quality degradation. For researchers, the dataset provides a base for numerical models validation, such as simplified thermal models and Computational Fluid Dynamics simulations. The international supply chain dataset is rare because of the complexity and the cost of implementation.
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Real-time dashboard monitoring and alerting system for compressed air supply in rubber compound manufacturer
(2020-01-01)
Thepmanee, Teerawat
;
Ngamsangiam, Pornprasert
;
Sittigorn, Jirasak
;
Pongswatd, Sawai
To minimize unexpected disruptions resulting from air supply problems in manufacturing production, a continuous monitoring of air pressures is crucial for predicting and preventing significant issues that may arise. This paper proposes a technique to build a real-time dashboard monitoring and alerting system for improving an availability of existing compressed air supply in a rubber compound manufacturer in Thailand. Flow and pressure transmitters as well as motorized ball valves are installed in the ma-jor supply lines of air piping system. In addition, a 3-phase power and energy meter is also installed to measure key electrical parameters of two main air compressors. The proposed technique is based on the use of cost-effective Node-RED web application not only to monitor volumetric flow rate, air pressure values, valve statuses, input/output module statuses, and energy-related parameters on the created dashboard in real time but also to alert plant personnel to pressure readings that fall outside an acceptable range via the LINE Notify application. There are three different notification patterns depending on how long is the pressure reading value out of the acceptable range. Moreover, the on/off status of all ball valves can also be remotely set on the dashboard subpages. Experimental results verify that the improved system can be utilized to assist plant personnel in trou-bleshooting and solving the problems with compressed air supply.

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