Gaetano Borriello

Location systems for ubiquitous computing

This survey and taxonomy of location systems for mobile-computing applications describes a spectrum of current products and explores the latest in the field. To make sense of this domain, we have developed a taxonomy to help developers of location-aware applications better evaluate their options when choosing a location-sensing system. The taxonomy may also aid researchers in identifying opportunities for new location-sensing techniques.

Bayesian filtering for location estimation

Bayesian-filter techniques provide a powerful statistical tool to help manage measurement uncertainty and perform multisensor fusion and identity estimation. The authors survey Bayes filter implementations and show their application to real-world location-estimation tasks common in pervasive computing.

Exploiting mobility for energy efficient data collection in wireless sensor networks

We analyze an architecture based on mobility to address the problem of energy efficient data collection in a sensor network. Our approach exploits mobile nodes present in the sensor field as forwarding agents. As a mobile node moves in close proximity to sensors, data is transferred to the mobile node for later depositing at the destination. We present an analytical model to understand the key performance metrics such as data transfer, latency to the destination, and power. Parameters for our model include: sensor buffer size, data generation rate, radio characteristics, and mobility patterns of mobile nodes. Through simulation we verify our model and show that our approach can provide substantial savings in energy as compared to the traditional ad-hoc network approach.

The location stack: a layered model for location in ubiquitous computing

Based on five design principles extracted from a survey of location systems, we present the location stack, a layered software engineering model for location in ubiquitous computing. Our model is similar in spirit to the seven-layer Open System Interconnect (OSI) model for computer networks. We map two existing ubiquitous computing systems to the model to illustrate the leverage the location stack provides. By encouraging system designers to think of their applications in this way, we hope to drive location-based computing toward a common vocabulary and standard infrastructure, permitting members of the ubiquitous computing community to easily evaluate and build on each others work.

Particle Filters for Location Estimation in Ubiquitous Computing: A Case Study

Location estimation is an important part of many ubiquitous computing systems. Particle filters are simulation-based probabilistic approximations which the robotics community has shown to be effective for tracking robots’ positions. This paper presents a case study of applying particle filters to location estimation for ubiquitous computing. Using trace logs from a deployed multi-sensor location system, we show that particle filters can be as accurate as common deterministic algorithms. We also present performance results showing it is practical to run particle filters on devices ranging from high-end servers to handhelds. Finally, we discuss the general advantages of using probabilistic methods in location systems for ubiquitous computing, including the ability to fuse data from different sensor types and to provide probability distributions to higher-level services and applications. Based on this case study, we conclude that particle filters are a good choice to implement location estimation for ubiquitous computing.

“Are You with Me?” – Using Accelerometers to Determine If Two Devices Are Carried by the Same Person

As the proliferation of pervasive and ubiquitous computing devices continues, users will carry more devices. Without the ability for these devices to unobtrusively interact with one another, the user’s attention will be spent on coordinating, rather than using, these devices. We present a method to determine if two devices are carried by the same person, by analyzing walking data recorded by low-cost MEMS accelerometers using the coherence function, a measure of linear correlation in the frequency domain. We also show that these low-cost sensors perform similarly to more expensive accelerometers for the frequency range of human motion, 0 to 10Hz. We also present results from a large test group illustrating the algorithm’s robustness and its ability to withstand real world time delays, crucial for wireless technologies like Bluetooth and 802.11. We present results that show that our technique is 100% accurate using a sliding window of 8 seconds of data when the devices are carried in the same location on the body, is tolerant to inter-device communication latencies, and requires little communication bandwidth. In addition we present results for when devices are carried on different parts of the body.

TiltType: accelerometer-supported text entry for very small devices

TiltType is a novel text entry technique for mobile devices. To enter a character, the user tilts the device and presses one or more buttons. The character chosen depends on the button pressed, the direction of tilt, and the angle of tilt. TiltType consumes minimal power and requires little board space, making it appropriate for wristwatch-sized devices. But because controlled tilting of ones forearm is fatiguing, a wristwatch using this technique must be easily removable from its wriststrap. Applications include two-way paging, text entry for watch computers, web browsing, numeric entry for calculator watches, and existing applications for PDAs.

The Chinook hardware/software co-synthesis system

Abstract: Designers of embedded systems are facing ever tighter constraints on design time, but computer-aided design tools for embedded systems have not kept pace with these trends. The Chinook co-synthesis system addresses the automation of the most time-consuming and error-prone tasks in embedded controller design, namely the synthesis of interface hardware and software needed to integrate system components, the migration of functions between processors or custom logic, and the co-simulation of the design before, during and after synthesis. This paper describes the principal elements of Chinook and discuss its application to a variety of embedded designs.

Next century challenges: data-centric networking for invisible computing: the Portolano project at the University of Washington

Computing and telecommunications are maturing, and the next century promises a shift away from technology-driven general-purpose devices. Instead, we will focus on the needs of consumers: easy-to-use, low-maintenance, portable, ubiquitous, and ultra-reliable task-specific devices. Such devices, although not as limited by computational speed or communication bandwidth, will instead be constrained by new limits on size, form-factor, and power consumption. Data that they generate will need to be injected into the Internet and find its way to the services to which the user has subscribed. This is not simply a problem of ad-hoc networking, but one that requires re-thinking our basic assumptions regarding network transactions and challenges us to develop entirely new models for distributed services. Network topologies will be intermittent and services will have to be discovered independently of user guidance. In fact, data transfers from user interfaces to services and back, will need to become invisible to the user and guided by the task rather than explicit commands. This paper outlines a vision of this future and identifies research problems that will require our attention in the areas of user interfaces, distributed services, and networking infrastructure.

WALRUS: wireless acoustic location with room-level resolution using ultrasound

In this paper, we propose a system that uses the wireless networking and microphone interfaces of mobile devices to determine location to room-level accuracy. The wireless network provides a synchronizing pulse along with information about the room. This is accompanied by an ultrasound beacon that allows us to resolve locations to the confines of a physical room (since audio is mostly bounded by walls). We generate the wireless data and ultrasound pulses from the existing PCs in each room; a PDA carried by a user listens for both signals. Thus, our approach does not require special hardware. We do not use ultrasound to send data. As a result we dramatically reduce the computational burden on the mobile device while also decreasing the latency of location resolution. Our results indicate that (i) ultrasound detection is robust even in noisy environments with many reflective surfaces; and (ii) that we can determine the correct room within a couple of seconds with high probability even when the ultrasound emitting PCs are not synchronized.