Development and Analysis of Low-Cost IoT Sensors for Urban Environmental Monitoring

The accelerated pace of urbanization is having a major impact over the world’s environment. Although urban dwellers have higher living standards and can access better public services as compared to their rural counterparts, they are usually exposed to poor environmental conditions such as air pollution and noise. In order for municipalities and citizens to mitigate the negative effects of pollution, the monitoring of certain parameters, such as air quality and ambient sound levels, both in indoor and outdoor locations, has to be performed. The current paper presents a complete solution that allows the monitoring of ambient parameters such as Volatile Organic Compounds, temperature, relative humidity, pressure, and sound intensity levels both in indoor and outdoor spaces. The presented solution comprises of low-cost, easy to deploy, wireless sensors and a cloud application for their management and for storing and visualizing the recorded data.

The Underwater Soundscape at Gulf of Riga Marine-Protected Areas

Passive acoustic monitoring (PAM) is widely used as an initial step towards an assessment of environmental status. In the present study, underwater ambient sound recordings from two monitoring locations in marine-protected areas (MPAs) of the Gulf of Riga were analysed. Both locations belong to the natural habitat of pinnipeds whose vocalisations were detected and analysed. An increase of vocal activity during the mating period in the late winter was revealed, including percussive signallings of grey seals. The ambient sound spectra showed that in the current shallow sea conditions ship traffic noise contributed more in the higher frequency bands. Thus, a 500 Hz one-third octave band was chosen as an indicator frequency band for anthropogenic noise in the monitoring area. It was shown that changes in the soundscape occurring during the freezing period create favourable conditions for ship noise propagation at larger distances. Based on the monitoring data, the environmental risks related to the anthropogenic sound around the monitoring sites were considered as low. However, further analysis showed that for a small percentage of time the ship traffic can cause auditory masking for the ringed seals.

Using Privacy Respecting Sound Analysis to Improve Bluetooth Based Proximity Detection for COVID-19 Exposure Tracing and Social Distancing

We propose to use ambient sound as a privacy-aware source of information for COVID-19-related social distance monitoring and contact tracing. The aim is to complement currently dominant Bluetooth Low Energy Received Signal Strength Indicator (BLE RSSI) approaches. These often struggle with the complexity of Radio Frequency (RF) signal attenuation, which is strongly influenced by specific surrounding characteristics. This in turn renders the relationship between signal strength and the distance between transmitter and receiver highly non-deterministic. We analyze spatio-temporal variations in what we call “ambient sound fingerprints”. We leverage the fact that ambient sound received by a mobile device is a superposition of sounds from sources at many different locations in the environment. Such a superposition is determined by the relative position of those sources with respect to the receiver. We present a method for using the above general idea to classify proximity between pairs of users based on Kullback–Leibler distance between sound intensity histograms. The method is based on intensity analysis only, and does not require the collection of any privacy sensitive signals. Further, we show how this information can be fused with BLE RSSI features using adaptive weighted voting. We also take into account that sound is not available in all windows. Our approach is evaluated in elaborate experiments in real-world settings. The results show that both Bluetooth and sound can be used to differentiate users within and out of critical distance (1.5 m) with high accuracies of 77% and 80% respectively. Their fusion, however, improves this to 86%, making evident the merit of augmenting BLE RSSI with sound. We conclude by discussing strengths and limitations of our approach and highlighting directions for future work.

Long Term Ambient Sound Level Survey

A 32 month long nighttime ambient sound level survey was conducted between from April 2017 and December 2019, inclusive. Sound level data was recorded at three locations within approximately 600 m of one another. Weather data was collected at one site. The measurement locations were at the edge of the city, where the suburbs make way for the countryside. Two noise monitoring stations were located near the back yards of detached houses. The third station was located in a more rural setting. This paper will look at trends in the nighttime ambient sound level (e.g. summertime vs wintertime), and try to establish the minimal duration of a measurement program for generating reliable results.

Spatial uniformity tolerances for sound masking systems in open-plan offices

Electronic sound masking systems raise the ambient sound level in offices to a controlled minimum sound level in order to increase speech privacy and reduce distractions. Sound masking systems are calibrated to provide the most uniform sound field achievable, as a spatially non-uniform masking sound field could result in occupant perception and uneven speech privacy conditions. Tolerances for acceptable spatial uniformity vary between specifiers, and may be based on different evaluation methods using only a few discrete measurement points to represent an entire office space. However, the actual uniformity of a masking sound field across an office, and the parameters influencing it, has not been widely investigated. Thus, this study aims to investigate the masking sound uniformity in a typical open-plan office space using fine-grid measurements conforming to measurement method of ASTM E1573-18. Percentages of measured locations where the sound pressure levels were within specified tolerances (with increments of 0.5 dB) were calculated using the measured 1/3 octave band levels. The research also utilized geometric acoustical simulations to investigate how physical office parameters (number of loudspeakers, partition heights, ceiling absorption, and diffusion characteristics) affect the sound field uniformity of the sound masking system.

Acoustical Conformance with FGI for Tenant Improvements in Outpatient, Medical Office or Clinic Facility Sound Isolation/Privacy Design

Acoustical privacy and noise control design and implementation guidance is needed, regarding Facility Guidelines Institute (FGI) criteria for outpatient medical facilty tenant improvements (TI). TI in existing commercial buildings or medical office buildings may not have capital budgets or expected facility/lease life that hospitals enjoy. Full conformance to FGI criteria and guidelines may be limited; by economic feasibility and by constructability. Design professionals can use "good practice" space planning, demising assembly selection, and electronic sound masking to achieve appropriate acoustical privacy within reasonable capital expense budgets. Consider FGI criteria for demising partition, ceiling, door and window selections plus infrastructure equipment and material selections that can provide cost-effective lightweight, common construction standards. The objectives are to protect the privacy of patient information and provide quiet spaces, free of transient disturbance for clear speech communications. Continuous ambient sound increases speech privacy including speech transmitted from enclosed quiet spaces. Criteria for acoustics, speech privacy,continuous noise and masking exists in FGI. Temporal level changes (on/off, transients) and tonality (spectrum smoothness or balance) should be considered in basis-of-design (BoD). This paper will present design guidelines for selecting demising assemblies and supplemental sound masking for outpatient clinical spaces in commercial or medical office buildings.