In recent years, many scholars have dedicated their research to the development of low-cost sensors for monitoring of various parameters. Despite their high number of applications, the state of the art related to low-cost sensors in building monitoring has not been addressed. To fill this gap, this article presents a systematic review, following well-established methodology, to analyze the state of the art in two aspects of structural and indoor parameters of buildings, in the SCOPUS database. This analysis allows to illustrate the potential uses of low-cost sensors in the building sector and addresses the scholars the preferred communication protocols and the most common microcontrollers for installation of low-cost monitoring systems. In addition, special attention is paid to describe different areas of the two mentioned fields of building monitoring and the most crucial parameters to be monitored in buildings. Finally, the deficiencies in line with limited number of studies carried out in various fields of building monitoring are overviewed and a series of parameters that ought to be studied in the future are proposed.

Nowadays, engineers are widely using accelerometers to record the vibration of structures for structural verification purposes. The main obstacle for using these data acquisition systems is their high cost, which limits its use to unique structures with a relatively high structural health monitoring budget. In this paper, a Cost Hyper-Efficient Arduino Product (CHEAP) has been developed to accurately measure structural accelerations. CHEAP is a system that is composed of five low-cost accelerometers that are connected to an Arduino microcontroller as their data acquisition system. Test results show that CHEAP not only has a significantly lower price (14 times cheaper in the worst-case scenario) compared with other systems used for comparison but also shows better accuracy on low frequencies for low acceleration amplitudes. Moreover, the final output results of Fast Fourier Transformation (FFT) assessments showed a better observable resolution for CHEAP than the studied control systems.

Today, low-cost sensors in various civil engineering sectors are gaining the attention of researchers due to their reduced production cost and their applicability to multiple nodes. Low-cost sensors also have the advantage of easily connecting to low-cost microcontrollers such as Arduino. A low-cost, reliable acquisition system based on Arduino technology can further reduce the price of data acquisition and monitoring, which can make long-term monitoring possible. This paper introduces a wireless Internet-based low-cost data acquisition system consisting of Raspberry Pi and several Arduinos as signal conditioners. This study investigates the beneficial impact of similar sensor combinations, aiming to improve the overall accuracy of several sensors with an unknown accuracy range. The paper then describes an experiment that gives valuable information about the standard deviation, distribution functions, and error level of various individual low-cost sensors under different environmental circumstances. Unfortunately, these data are usually missing and sometimes assumed in numerical studies targeting the development of structural system identification methods. A measuring device consisting of a total of 75 contactless ranging sensors connected to two microcontrollers (Arduinos) was designed to study the similar sensor combination theory and present the standard deviation and distribution functions. The 75 sensors include: 25 units of HC-SR04 (analog), 25 units of VL53L0X, and 25 units of VL53L1X (digital).

The non-destructive thermal characterization of building envelopes relies significantly on various factors such as climate conditions, monitoring devices used, indoor environment, and conditioning systems. In the case of both the temperature-based method (TBM) and heat flux meter (HFM) approaches, U-value is determined considering the ideal condition of steady state. However, it is challenging to accurately define the true thermal condition of buildings when monitoring is affected by inherent uncertainties of the chosen approach and inadequate instrumentation of building envelopes. This paper presents the outcomes of an experimental campaign, that aimed to evaluate the impact of incorrectly positioned exterior sensors, on the precision of U-value measurements. This study simultaneously employed the TBM and HFM approaches. To enhance the accuracy of the results, rigorous outlier detection and statistical analysis were employed on the data collected from three autonomous monitoring systems. The findings of this study revealed that the applied data analysis yielded more satisfactory results for the TBM approach compared to HFM. However, regardless of the approach used, the effectiveness of outlier detection relied heavily on the accuracy of the monitoring systems. When removing an individual outlier, the monitoring systems characterized with higher accuracies provided U-values that were closer to the theoretical values, than less accurate ones.

In structures with reduced monitoring budgets, the high cost of commercial metering devices is always an obstacle for monitoring structural health. This might be an issue when temperatures must be measured for both structural and environmental reasons. To fill this gap, in this paper, a novel monitoring system is proposed for the accurate measurement of indoor temperature in buildings. This protocol is characterized by its generality, as it can be easily adapted to measure any structural or environmental parameters on site. The proposed monitoring system uses from one to eight low-cost sensors to obtain multiple measurements of the ambient temperatures. The accuracy ranges of the developed monitoring systems with different numbers of sensors are statistically analysed. The results indicate that the discrepancy of the measurements decreases with the increase in the number of sensors, as the maximum standard deviation of 10 sensors (0.42) decreases to 0.32 and 0.27 for clusters of 20 and 30 sensors, respectively.

Owing to the high energy consumption in the building sector, appraising the thermal performance of building envelopes is an increasing concern. Recently, a few in situ methodologies to diagnose the thermal parameters of buildings have been considered. However, because of their limitations such as low accuracy, limited number of measurements, and the high cost of monitoring devices, researchers are seeking a new alternative. In this study, a novel hyper-efficient Arduino transmittance-meter was introduced to overcome these limitations and determine the thermal parameters of building envelopes. Unlike conventional methodologies, the proposed transmittance-meter is based on synchronized measurements of different parameters necessary to estimate the transmittance parameter. To verify the applicability of the transmittance-meter, an experimental study was conducted wherein a temperature-controlled box model was thermally monitored, and the outputs of the transmittance-meter employed were compared with those captured by a commercial device. The results revealed a high level of reduction in cost and a low range of difference compared with the latter, thereby validating the applicability of the proposed thermal monitoring system.