Temperature logger

1998 ◽  
Vol 96 (6) ◽  
pp. 146
Keyword(s):  
Temperature Logger

scholarly journals Evaluation and Recommendations for Improving the Accuracy of an Inexpensive Water Temperature Logger

2013 ◽  
Vol 30 (7) ◽  
pp. 1576-1582 ◽  
Author(s):  
S. J. Lentz ◽  
J. H. Churchill ◽  
C. Marquette ◽  
J. Smith
Keyword(s):  
Surface Layer ◽  
Solar Radiation ◽  
Water Temperature ◽  
Solar Heating ◽  
Bias Error ◽  
Mean Square ◽  
Temperature Logger ◽  
Accurate Temperature ◽  
Rms Error ◽  
Rms Errors

Abstract Onset's HOBO U22 Water Temp Pros are small, reliable, relatively inexpensive, self-contained temperature loggers that are widely used in studies of oceans, lakes, and streams. An in-house temperature bath calibration of 158 Temp Pros indicated root-mean-square (RMS) errors ranging from 0.01° to 0.14°C, with one value of 0.23°C, consistent with the factory specifications. Application of a quadratic calibration correction substantially reduced the RMS error to less than 0.009°C in all cases. The primary correction was a bias error typically between −0.1° and 0.15°C. Comparison of water temperature measurements from Temp Pros and more accurate temperature loggers during two oceanographic studies indicates that calibrated Temp Pros have an RMS error of ~0.02°C throughout the water column at night and beneath the surface layer influenced by penetrating solar radiation during the day. Larger RMS errors (up to 0.08°C) are observed near the surface during the day due to solar heating of the black Temp Pro housing. Errors due to solar heating are significantly reduced by wrapping the housing with white electrical tape.

Usefulness and limitation of a tiny light-temperature logger to monitor daily activity levels of arboreal squirrels in temperate areas

2017 ◽  
Vol 62 (4) ◽  
pp. 397-404 ◽  
Author(s):  
Jason L. Anders ◽  
Kenta Uchida ◽  
Mitsuru Watanabe ◽  
Iori Tanio ◽  
Tatsuki Shimamoto ◽  
...  
Keyword(s):  
Daily Activity ◽  
Activity Levels ◽  
Temperature Logger

scholarly journals Use of Multiple Temperature Logger Models Can Alter Conclusions

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 668
Author(s):  
Joanna B. Whittier ◽  
Jacob T. Westhoff ◽  
Craig P. Paukert ◽  
Robin M. Rotman
Keyword(s):  
Water Quality ◽  
Regulatory Compliance ◽  
Effect Of Temperature ◽  
Regulatory Agencies ◽  
Water Quality Standards ◽  
Temperature Logger ◽  
Combined Model ◽  
Combining Data ◽  
Ecological Implications ◽  
Similar Accuracy

Remote temperature loggers are often used to measure water temperatures for ecological studies and by regulatory agencies to determine whether water quality standards are being maintained. Equipment specifications are often given a cursory review in the methods; however, the effect of temperature logger model is rarely addressed in the discussion. In a laboratory environment, we compared measurements from three models of temperature loggers at 5 to 40 °C to better understand the utility of these devices. Mean water temperatures recorded by logger models differed statistically even for those with similar accuracy specifications, but were still within manufacturer accuracy specifications. Maximum mean temperature difference between models was 0.4 °C which could have regulatory and ecological implications, such as when a 0.3 °C temperature change triggers a water quality violation or increases species mortality rates. Additionally, precision should be reported as the overall precision (including a consideration of significant digits) for combined model types which in our experiment was 0.7 °C, not the ≤0.4 °C for individual models. Our results affirm that analyzing data collected by different logger models can result in potentially erroneous conclusions when <1 °C difference has regulatory compliance or ecological implications and that combining data from multiple logger models can reduce the overall precision of results.

scholarly journals Robonerite: A low-cost biomimetic temperature logger to monitor operative temperatures of a common gastropod (Nerita spp.) in tropical urban seascapes

HardwareX ◽  
2019 ◽  
Vol 6 ◽  
pp. e00075 ◽  
Author(s):  
Shelley H.M. Chan ◽  
Lynette H.L. Loke ◽  
Sam Crickenberger ◽  
Peter A. Todd
Keyword(s):  
Low Cost ◽  
Temperature Logger ◽  
Operative Temperatures

Temperature logger for Electrical Equipment's Thermal Stress Monitoring

2019 ◽  
Author(s):  
Alin Dragomir ◽  
Maricel Adam ◽  
Mihai Andrusca ◽  
Cosmin Nistor Deac ◽  
Anamaria Iamandi
Keyword(s):  
Thermal Stress ◽  
Stress Monitoring ◽  
Temperature Logger

Design of the Improved Accompanying Temperature Logger

2014 ◽  
Vol 989-994 ◽  
pp. 3015-3018
Author(s):  
Juan Guo ◽  
Shi Ying Liang ◽  
Zong Tao Yin
Keyword(s):  
Power Consumption ◽  
Energy Conservation ◽  
Low Power ◽  
Communication Protocol ◽  
Reducing Power ◽  
Experimental Tests ◽  
Low Power Consumption ◽  
Temperature Logger ◽  
Ultra Low Power

This paper describes research on some methods of reducing power consumption to reduce the volume accompanying logger. For the requirement of ultra-low power consumption and miniature, the design is described separately from the hardware and software, mainly including temperature detecting module, interface of communication, low current circuit hardware, energy conservation ,arouse from power down state, communication protocol, etc. The experimental tests for device prove that the research can achieve low power requirements.

scholarly journals SEASONAL AND INTRA-SEASONAL VARIABILITY OF SEA SURFACE TEMPERATURE IN PARI ISLAND-JAKARTA, INDONESIA

2019 ◽  
Vol 12 (1) ◽  
pp. 97
Author(s):  
Corry Corvianawatie
Keyword(s):  
Time Series ◽  
Seasonal Variability ◽  
Continuous Measurement ◽  
Seasonal Pattern ◽  
Sea Surface ◽  
Madden Julian Oscillation ◽  
Temperature Logger ◽  
Marine Life ◽  
Double Peaks ◽  
Oceanographic Parameter

<p>Sea Surface Temperatures (SSTs) is one of the most important oceanographic parameter that could affect the marine life, especially coastal ecosystem. SSTs data varies in hourly, daily, seasonal, annual, inter-annual, and even in longer time scales. This condition makes any studies using instantaneous measurement could turn into misleading report due to the lack of time series SSTs data. Thus, the aim of this study is to understand the seasonal and intra-seasonal SSTs dynamics in Pari Island using continuous measurement from temperature logger. This study found that the double peaks of SSTs in May and November are correspond to the period of transitional monsoon. Conversely, the two minimum SSTs in February and August were correspond to the peak of northwest monsoon and southeast monsoon respectively. In addition to seasonal pattern, the slightly dominant intra-seasonal variability of SSTs was found in the period of 57 and 86 days. Those predominant signals suggested represent the Madden-Julian Oscillation phenomena.</p>

scholarly journals Shipping and storage temperature logger datasets for extended shelf life vacuum packaged chilled beef in the Chinese supply chain

Data in Brief ◽  
2019 ◽  
Vol 27 ◽  
pp. 104586 ◽  
Author(s):  
Damian Frank ◽  
Yimin Zhang ◽  
Xin Luo ◽  
Xue Chen ◽  
Glen Mellor ◽  
...  
Keyword(s):  
Supply Chain ◽  
Shelf Life ◽  
Storage Temperature ◽  
Temperature Logger ◽  
And Storage
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