William F. Jerome

Remote health-care monitoring using personal care connect

Caring for patients with chronic illnesses is costly-nearly

Enabling location-based applications

1.27 trillion today and predicted to grow much larger. To address this trend, we have designed and built a platform, called Personal Care Connect (PCC), to facilitate the remote monitoring of patients. By providing caregivers with timely access to a patients health status, they can provide patients with appropriate preventive interventions, helping to avoid hospitalization and to improve the patients quality of care and quality of life. PCC may reduce health-care costs by focusing on preventive measures and monitoring instead of emergency care and hospital admissions. Although PCC may have features in common with other remote monitoring systems, it differs from them in that it is a standards-based, open platform designed to integrate with devices from device vendors and applications from independent software vendors. One of the motivations for PCC is to create and propagate a working environment of medical devices and applications that results in innovative solutions. In this paper, we describe the PCC remote monitoring system, including our pilot tests of the system.

Context-aware and personalized event filtering for low-overhead continuous remote health monitoring

We identify a number of factors that may hinder the commercial success of location-based applications: the concern of privacy, the need to consider context beyond location, the presence of voluminous resources, and the constrained interfaces available on mobile devices. We describe an end-to-end system architecture with integrated support to address these issues. In particular, the architecture includes a Secure Context Service that provides broad context information to applications and allows people to flexibly control the release of their private information, an Intelligent Service Discovery Service that allows for personalized selection of physical and virtual services, and a multi-modal interaction mechanism that enables users to exploit multiple synchronized access channels to interact with an application and to switch among channels at any time. Our goals are to improve user experience, to reduce user distraction and to facilitate awareness of the physical world.

Privacy Engine for Context-Aware Enterprise Application Services

A particularly compelling vision of long-term remote health monitoring advocates the use of a personal pervasive device (such as a cellphone) as an intermediate relay, which transports data streams from multiple body-worn sensors to a backend analytics infrastructure. Unfortunately, a pure relay-based functionality on the cellphone is inadequate in the longer term, as increasingly sophisticated medical sensors impose unnacceptably high uplink traffic and energy consumption costs on the mobile device. To address this challenge, we are building an event-processing middleware, called HARMONI, which enables the pervasive device to perform context-aware processing and event filtering on the sensor data streams and locally extract higher-level features of interest, thereby reducing the volume of transmitted data. This paper presents the design and architectural components of HARMONI, with special emphasis on its implementation of context-aware event processing. This paper then demonstrates that the mobile device can extract localized context from the incoming sensor stream with sufficient accuracy to achieve satisfactory context-aware filtering. Our results also establish the need for personalizing such context extraction, as they show that similar sensor data patterns obtained from different individuals can imply significantly different activity contexts.

Active middleware services in a decision support system for managing highly available distributed resources

Satisfying the varied privacy preferences of individuals, while exposing context data to authorized applications and individuals, remains a major challenge for context-aware computing. This paper describes our experiences in building a middleware component, the context privacy engine (CPE), that enforces a role-based, context-dependent privacy model for enterprise domains. While fundamentally an ACL-based access control scheme, CPE extends the traditional ACL mechanism with usage control and context constraints. This paper focuses on discussing issues related to managing and evaluating context-dependent privacy policies. Extensive experimental studies with a production-grade implementation and real-life context sources demonstrate that the CPE can support a large number of concurrent requests. The experiments also show valuable insight on how context-retrieval can affect the privacy evaluation process.

Managing a cluster of networked resources and resource groups using rule - base constraints in a scalable clustering environment

We describe a decision support system called Mounties that is designed for managing applications and resources using rule-based constraints in scalable mission-critical clustering environments. Mounties consists of four active service components: (1) a repository of resource proxy objects for modeling and manipulating the cluster configuration; (2) an event notification mechanism for monitoring and controlling interdependent and distributed resources; (3) a rule evaluation and decision processing mechanism; and (4) a global optimization service for providing decision making capabilities. The focus of this paper is on the design of the first three services that together connect and coordinate the distributed resources with the decision making component. We discuss the overall architecture and design of these services. We describe in some detail the asynchronous, concurrent, and pipelined nature of their interactions and the fault tolerance designed in the system. We also describe a general programming paradigm that we have followed in designing these services.