Middleware for assisted living homes (MiddAALware)

Many countries are grappling with the complexities of an ageing population, a challenge that ambient assisted living (AAL) technologies aim to mitigate. Typically, AAL systems employ middleware to facilitate integration among diverse devices. However, current middleware solutions tend to be large and are designed for expansive smart systems, which is less than ideal for the more modest scale of AAL homes targeted at individuals, such as those with early-stage dementia. The development of personalised and adaptive AAL systems necessitates middleware that is both flexible and lightweight, enabling deployment in environments with limited resources. This MRes project investigates a lightweight middleware solution for AAL systems, aiming to offer adaptable and efficient integration options for AAL home platforms. By embracing a minimalist design approach, this software is designed to perform optimally in resource-restricted settings. The middleware was implemented within the SEArch and Smart Spaces Lab at Middlesex University, alongside a real-time event reasoner, a location detection system, and a behaviour learning module. This setup facilitated improved interoperability among these components. Opting for an event-based middleware architecture over message-oriented or service-oriented alternatives, enables enhanced processing, routing, and data transformation capabilities within the SEArch system architecture. To assess the middleware's effectiveness, three smart automation scenarios simulating daily activities were conducted to illustrate the middleware’s proficiency. These tests illustrated the middleware's proficiency in communicating with the various elements of the SEArch system architecture and demonstrated its efficiency.