# Noise Impact Analysis of School Environments Based on the Deployment of IoT Sensor Nodes
###### Abstract
However, the adoption of IoT technologies in education raises several concerns about data privacy, especially concerning the monitoring of pupils or students, and therefore additional precautions should be considered [13]. It is important to follow regular calibration and maintenance procedures to ensure the reliability and accuracy of the sensor measurements as dictated in [14]. The time of daily operation in school units could be divided into two categories: (a) _in-class operation_, which will be simply termed _\"lesson time\"_ and (b) _out-of-class period_ that is defined as _\"break\"_. Usually when focusing on the functioning conditions of pupils and teachers in a school unit, we mainly consider lesson time. It is important to state that during that period, the operation is closely supervised and controlled by the classroom teacher. Despite the forming of a multifactorial and volatile environment during the lesson time which is shaped by many different aspects, such as the type of lesson, the action performed, and the interior design, it is noticeable that it is strictly controlled and supervised by the teacher. Breaks, on the other hand, which introduce an important part (about 20%) of a school day, are of no guided restrictions, and consequently, situations of intense mobility and high noise frequently develop. These noisy circumstances affect the working environment of teachers and some pupils, particularly when they exceed the tolerable limits, distressing their psychological and physical health, as well as their social behavior [5; 15]. Moreover, the average age of teachers is about 50 years old, and burnout syndromes are very common. Drawing from the aforementioned analysis, the aim of this work is to implement a sensor network, based on the Internet of Things technology, forming, in this way, a vehicle for measuring noise and other environmental conditions [16] of school complexes. We have particularly focused on monitoring noise conditions during breaks, also taking into account the conditions of building infrastructure and how it can potentially isolate noise levels. In contrast to the works performed in [4, 5, 6], where generally the chosen building facilities were in poor to moderate condition depending on their age, we have selected school complexes that have been recently renovated based on current standards to minimize the energy footprint and carbon emissions to the environment. Therefore, our target is to show that mitigation of high noise levels in urban areas and especially in school buildings should also be taken as a criterion during construction or renovations, apart from CO\({}_{2}\) friendliness. To this end, the objectives/contributions of this study are synopsized below:  
* Design of IoT infrastructure for noise tracking in school buildings;
* Explore whether energy upgrades and thermal isolation in school infrastructures mitigate the extensive noise levels in comparison to the work reported in the literature;
* Further evaluate the noise behavior through statistical analysis of the stored sensor data;
* Impact assessment of the noise and its effects during the course breaks;
* Propose guidelines on supplementary improvements in renovated school buildings to further isolate noise and how the proposed IoT solution could be a useful tool to serve this purpose. The rest of the paper is organized as follows. Section 2 presents the methods used to conduct this research, the IoT architecture, and its building deployments. Section 3 analyzes the generated results, while Section 4 evaluates the performance of the IoT infrastructure installed and also assesses the measurements received from the low-cost sensors. Finally, Section 5 concludes our work.