Wireless sensor networks can provide a cheap and flexible infrastructure to support the measurement of noise pollution. However, the processing of the gathered data is challenging to implement on resource-constrained nodes, because each node has its own limited power supply, low-performance and low-power micro-controller unit and other limited processing resources, as well as limited amount of memory. We propose a sensor node for monitoring of indoor ambient noise. The sensor node is based on a hardware platform with limited computational resources and utilizes several simplifications to approximate more complex and costly signal processing stage. Furthermore, to reduce the communication between the sensor node and a sink node, as well as the power consumed by the IEEE 802.15.4 (ZigBee) transceiver, we perform digital A-weighting filtering and non-calibrated calculation of the sound pressure level on the node. According to experimental results, the proposed sound level meter can accurately measure the noise levels of up to 100 dB, with the mean difference of less than 2 dB compared to Class 1 sound level meter. The proposed device can continuously monitor indoor noise for several days. Despite the limitations of the used hardware platform, the presented node is a promising low-cost and low-power solution for indoor ambient noise monitoring.

The existing methods of automated building management are faced with critical challenges in the modern smart grid movement. Remote data transmission, efficient data processing and the ability to adapt rapidly to changes are severely limited as a result of the poor connectivity and rigidity of the existing systems. As an effective solution to such challenges, a new generation of smart micro- controller systems has been designed, which in addition to the above-described factors delivers many new features and holds yet relatively unexplored potentials for further development. The major advantage of these systems is integration with a cloud service that already enables the more efficient management of remote buildings and delivers enhanced user and environment-friendly solutions. In addition, with the quick adaptation ability, these systems also offer effective solutions for new, yet unforeseen, smart building challenges in the future. In the first part of this article, we present the basic module for controlling an individual smart building and its integration into the wider concept of smart grids and smart city networks: DIALOG EQ microcontroller system, which is aimed at the efficient, distributed management of smart buildings. We describe the process of its development and current capabilities. The basic guideline for the development was user and environment friendliness. The second part is dedicated to the development potentials of the system, the challenges of the future and certain aspects of automatic (machine) learning from the data obtained through the operation of these systems in individual buildings.