Stephen D. Pipes

Smart building management through augmented reality

This paper presents a software architecture for Smart Buildings assets management which enables engineers to receive and update work orders and asset information using augmented reality and mobile technologies. The proposed architecture consists of a layered structure composed of three main modules for Building Management Systems (BMS); data collection, event management and enrichment, and asset and work order management. In this architecture we use the Message Queue Telemetry Transport protocol (MQTT) to exchange messages between the system components. Work orders and alerts are modelled using the Common Alert Protocol (CAP) and sent to the augmented reality application through the ITA Information fabric; a middleware component using MQTT augmented with policy, workflow and datastore. We describe the high-level architecture supporting the experimentation and services provision, access policies and security aspects of such an architecture. This architecture can encapsulate the system functionality, assure the interoperability between various component systems, integrate different data standards, and ease the maintenance, management and upgrading of building assets and service requests. The design of a smart building application based on this architecture is illustrated and experimentation results confirm the viability and efficiency of the proposed framework.

Multitiered inference management architecture for participatory sensing

This paper describes a multitiered architecture for realizing an inference management firewall (IMF) that employs context-aware information masking techniques for systematic management of risk-vs-value trade-off of sensor data. Previously we have demonstrated an initial implementation of the IMF running as messaging services on the Information Fabric, which is a middleware asset developed under the International Technology Alliance (ITA) research program. Furthermore, we have presented an additional asset, recently implemented on a commercially-available mobile device running the Android operating system, which is intended to operate as an information source and first-line inference management capability at the edge of the network. The low-cost and widespread use of Android-based mobile devices offers a popular platform for crowdsourced participatory sensing. The focus of our current work is on the integration of these two technology assets in support of policy-managed, sensor-driven workflows in coalition scenarios.