Occupancy Estimation Using Low-Cost Wi-Fi Sniffers

Real-time measurements on the occupancy status of indoor and outdoor spaces can be exploited in many scenarios (HVAC and lighting system control, building energy optimization, allocation and reservation of spaces, etc.). Traditional systems for occupancy estimation rely on environmental sensors (CO2, temperature, humidity) or video cameras. In this paper, we depart from such traditional approaches and propose a novel occupancy estimation system which is based on the capture of Wi-Fi management packets from users' devices. The system, implemented on a low-cost ESP8266 microcontroller, leverages a supervised learning model to adapt to different spaces and transmits occupancy information through the MQTT protocol to a web-based dashboard. Experimental results demonstrate the validity of the proposed solution in four different indoor university spaces.Comment: Submitted to Balkancom 201

Comparison of spectrum occupancy measurements using software defined radio RTL-SDR with a conventional spectrum analyzer approach

In the present day Cognitive Radio has become a realistic option for solution of the spectrum scarcity problem in wireless communication. Recently, the TV band has attracted attention due to the considerable potential for exploitation of available TV white space which is not utilized based on time and location. In this paper, we investigate spectrum occupancy of the UHF TV band in the frequency range from 470 to 862MHz by using two different devices, the low cost device RTL-SDR and high cost spectrum analyzer. The spectrum occupancy measurements provide evidence of the utility of using the inexpensive RTL SDR and illustrate its effectiveness for detection of the percentage of spectrum utilization compared with results from the conventional high cost Agilent spectrum analyzer, both systems employing various antennas

A Simple Model of Housing Rental and Ownership with Policy Simulations

The housing market is both large and complex. This paper develops a simple model that captures the essential features of the supply and demand for housing, and which is used to evaluate the impact of a range of policy interventions. Increases in the stock of housing would reduce rents and house prices. A reduction in tax concessions for landlords would raise rents and moderate house prices. Additional subsidies for owner-occupancy would tend to reduce rents and raise house prices. Significant reductions in rents and house prices would follow a fall in the cost of housing, through, for example lower regulatory and consent costs. Falling real interest rates result in lower rents, higher house prices and lower owner-occupancy rates. Despite the widespread attention owner-occupancy rates have attracted, the paper concludes that they are not a particularly helpful guide to the state of the housing market. Typically they are quite insensitive to policy interventions, a result that follows from the integrated view of both the rental and ownership market, adopted in this study.Housing markets; New Zealand; rental and owner-occupancy; elasticities; rents; house prices; policy simulations

Wavelet-based filtration procedure for denoising the predicted CO2 waveforms in smart home within the Internet of Things

The operating cost minimization of smart homes can be achieved with the optimization of the management of the building's technical functions by determination of the current occupancy status of the individual monitored spaces of a smart home. To respect the privacy of the smart home residents, indirect methods (without using cameras and microphones) are possible for occupancy recognition of space in smart homes. This article describes a newly proposed indirect method to increase the accuracy of the occupancy recognition of monitored spaces of smart homes. The proposed procedure uses the prediction of the course of CO2 concentration from operationally measured quantities (temperature indoor and relative humidity indoor) using artificial neural networks with a multilayer perceptron algorithm. The mathematical wavelet transformation method is used for additive noise canceling from the predicted course of the CO2 concentration signal with an objective increase accuracy of the prediction. The calculated accuracy of CO2 concentration waveform prediction in the additive noise-canceling application was higher than 98% in selected experiments.Web of Science203art. no. 62

Comparative efficacy of sign surveys, spotlighting and audio playbacks in a landscape-scale carnivore survey

Many carnivores are difficult and labour-intensive to detect, often leading to prohibitively high effort and cost in large-scale surveys. However, such studies provide information that is important for effective management and conservation. Here, we evaluate the suitability of three survey methods for landscape-scale multi-species monitoring. We compare sign surveys, spotlighting, and audio playbacks in terms of detection efficiency, precision, effort, and cost. Sign surveys out-performed the other methods in all comparison criteria, although supplementary methods were needed for some species and sites. We found that using established analysis techniques, robust landscape-scale abundance estimates would require unrealistically high effort and cost. Occupancy estimation required considerably lower sample sizes and was therefore more economical. We conclude that sign-based occupancy estimates constitute a versatile and efficient option for future large-scale, multi-species carnivore surveys

A Simple Model of Housing Rental and Ownership with Policy Simulations

This paper develops a simple model that captures the essential features of the supply and demand for housing, and which is used to evaluate the impact of a range of policy interventions. The model incorporates functions describing the demand to rent or purchase housing, a function describing the supply of rental housing, and a function describing the supply of new houses. The model is used to explore the effects on prices, quantities, and owner occupancy (homeownership) rates of policies that change the stock of housing, that alter the taxes and subsidies facing landlords and homeowners, that alter the cost of new housing, and that alter real interest rates. The results suggest that despite the widespread attention owner occupancy rates have attracted, they are not a particularly helpful guide to the state of the housing market. Typically they are quite insensitive to policy interventions, a result that follows from the integrated view of both the rental and ownership market, adopted in this study.Housing markets; New Zealand; rental and owner occupancy; elasticities; rents; house prices; policy simulations