2019
DOI: 10.1051/matecconf/201928202039
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A low-cost wireless sensor network for long term monitoring of energy performance and sustainability of buildings

Abstract: This manuscript describes the development of a wireless sensor system for long term monitoring of temperature, humidity and heat flux reading within building structural elements, including places that are hard to reach using wired sensors. The system was tested in cold Latvian climate in 3 different buildings. The main objectives during the development phase were the maximization of network operational lifetime, ensurance of work stability and maintenance cost reduction to make the system feasible for wide use… Show more

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Cited by 4 publications
(3 citation statements)
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“…An outside weather station allows to get the temperature outside. An extended description of the measuring system is given in [10].…”
Section: Verificationmentioning
confidence: 99%
“…An outside weather station allows to get the temperature outside. An extended description of the measuring system is given in [10].…”
Section: Verificationmentioning
confidence: 99%
“…For the dynamic evaluation of U value changes, heat flux sensors (W 150-s) were installed on the wall, whose properties were evaluated in the previous paragraph. The details about monitoring system for heat flux measurements could be found in [19]. For delta temperature evaluation, the temperatures used were the weather station temperature and the temperature from sensor (sht35) located in the middle of the room.…”
Section: Heat Flux Data Pre-processingmentioning
confidence: 99%
“…Determining the optimal NN hyperparameters is still an unresolved problem in neural networks. The universal approximation theorem states that an NN with a linear output layer and at least one hidden layer with any activation function (e.g., a sigmoid activation function) can approximate any function from one finite dimensional space to another with any desired non-zero error value, if enough hidden units are allocated [19]. In turn, only linear functions can be approximated by NN with only one layer.…”
Section: Evaluation Of Dynamic U With Nnmentioning
confidence: 99%