Nicholas M. Boers

Software engineering for health education and care delivery systems: The Smart Condo project

Providing affordable, high-quality healthcare to the elderly while enabling them to live independently longer is of critical importance, as this is an increasing and expensive demographic to treat. Sensor-network technologies are essential to developing assisted living environments. In our Smart Condo project, we have deployed a sensor network with a variety of sensor types in an 850 square-foot condominium. The sensor network records a variety of events and environmental parameters and feeds the related data into our web-based system. This system is responsible for inferring higher-order information about the activities of the condos occupant and supporting the visualization of the collected information in a 2D Geographic Information System (GIS) and a 3D virtual world, namely Second Life (SL).

The smart condo: visualizing independent living environments in a virtual world

Providing affordable, high-quality healthcare to the elderly while enabling them to live independently longer is of critical importance. In our Smart Condo project, we have deployed a wireless sensor network in an 850-square-foot condominium for assisted living. The sensor network records a variety of events and environmental parameters and feeds the related data into our web-based system. This system is responsible for inferring higher-order information about the activities of the condos occupant and visualizing the collected information in both a 2D Geographic Information System (GIS) and a 3D virtual world. The architecture is flexible in terms of supported sensor types, analyses, and visualizations through which it communicates this information to its users, including the condos occupant, their family, and their healthcare providers.

Sampling and classifying interference patterns in a wireless sensor network

The low-powered transmissions in a wireless sensor network (WSN) are highly susceptible to interference from external sources. Our work is a step towards enabling WSN devices to better understand the interference in their environment so that they can adapt to it and communicate more efficiently. We extend our previous work in which we collected received signal strength traces using mote-class synchronized receivers at sample rates that are, to the best of our knowledge, higher than previously described in the literature. These traces contain distinct interference patterns, each with a different potential for being exploited by cognitive radio strategies. In order to exploit a pattern, however, a node must first recognize it. Given the energy and space constraints of a node, we explore succinct decision tree classifiers for the two most disruptive patterns. We expand on a basic feature set to incorporate attributes based on the dip statistic and the Lomb periodogram, both of which address specific, empirically observed behaviour, and we show their positive impact on both the decision tree structure and the overall classification performance. Moreover, we present an approximation of the periodogram that makes its construction feasible for mote-class devices, and we describe the simplifications impact on classification performance.

Patterns in the RSSI traces from an indoor urban environment

Urban environments are notorious for their high spectrum usage, particularly in their unlicensed radio bands. Wireless sensor network (WSN) nodes incorporate modern transceivers that can measure the background noise/interference and change channels. These combined capabilities suggest the need to better understand urban environments so that nodes can better avoid competing devices. In this paper, we explore the noise and interference patterns found on 256 frequencies in an indoor urban environments 900 MHz ISM and non-ISM bands. We begin the process by using off-the-shelf WSN hardware to sample the environment at 5 kHz from 16 locations simultaneously. From these samples, we identify five prevalent patterns and then hand-classify the 4096 traces of noise and interference. Finally, we extract a variety of statistics from the traces and use them in a Bayesian network classifier.

Developing wireless sensor network applications in a virtual environment

We describe our “holistic” platform for developing wireless ad hoc sensor networks and focus on its most representative and essential virtualization component: VUE2 (the Virtual Underlay Emulation Engine). Its role is to provide a vehicle for the authoritative emulation of complete networked applications before physically deploying any wireless nodes. The goal is to be able to verify those applications exhaustively before programming the hardware, such that no further (field) tests are necessary. We explain how VUE2 achieves this goal owing to several facilitating factors, most notably the powerful programming paradigm that our platform adopts. As implied by the holistic nature of the discussed system, our work touches upon operating systems, simulation, network protocols, real-time systems, and programming methodology.

Supporting wireless application development via virtual execution

We introduce our ldquoholisticrdquo platform for building wireless ad hoc sensor networks and focus on its most representative and essential virtualization component: VUE2 (the Virtual Underlay Emulation Engine). Its role is to provide a vehicle for authoritative emulation of complete networked applications before physically deploying the wireless nodes. The goal is to be able to verify those applications exhaustively before programming the hardware, such that no further (field) tests are necessary. We explain how VUE2 achieves this goal owing to several facilitating factors, most notably the powerful programming paradigm adopted in our platform. As implied by the holistic nature of the discussed system, our presentation touches upon operating systems, simulation, network protocols, real-time systems, and programming methodology.

An Automation of Mail Channels

Mail channels allow an electronic mail (e-mail) user to have multiple points of contact, each with a potentially different policy. For example, a user may have two channels, one for personal use and one for business use. The former channel’s policy may accept all senders and the latter channel’s may restrict senders to those within a given company. By extending this example, an e-mail user can have a channel unique to each contact, each with a policy that restricts its use to the particular contact. Traditionally, this scenario requires substantial administrative overhead, making it impractical. The system described here, the Spam Free Mail (SFM) service (see https://sfm.cs.ualberta.ca), automates the creation of mail channels. Its restrictive mail channels effectively eliminate a considerable part of e-mail abuse, such as spam and phishing.

Impact of orientation and wire placement on received signal strengths

Many radio transceivers provide an instantaneous measure of radio-frequency (RF) energy through their received signal strength indicator (RSSI) output. Applications of this measurement include media access control (MAC), e.g., implemented as listen-before-talk (LBT), and location estimation. Factors both internal and external to wireless devices may significantly impact these measurements, and much work involving RSSI measurements glosses over this fact. This paper explores how three specific factors, (a) (omnidirectional) antenna orientation, (b) node orientation, and (c) node wire position, impact RSSI measurements. The results show a significant impact for both node orientation and node wire position and an insignificant impact for (omnidirectional) antenna orientation.

A Distributed Time-Domain Approach to Mitigating the Impact of Periodic Interference

Low-powered wireless transmissions, such as those of a wireless sensor network WSN, are particularly susceptible to radio-frequency RF interference. When the interference exhibits regularities amounting to perceptible patterns, e.g.,i¾?regularly-spaced short-duration impulses that correlate among multiple network nodes, opportunities exist for nodes to avoid impulses and consequently mitigate their negative impact on the packet reception rate. Rather than adopt special hardware for classification and mitigation, which is often done with cognitive radios, our research explores techniques that can enhance the medium access control schemes of the traditional off-the-shelf RF modules typically found in low-cost WSN nodes. This paper describes a distributed time-domain approach for identifying the periodicity of impulses and scheduling transmissions around them. The approach is evaluated using a simulator in terms of packet reception rates and latency, and the results show that it can significantly reduce packet losses.