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This project aims to demonstrate the technical feasibility and benefits of an in-home early warning system for detecting increased frailty in elderly individuals. The product, Ally, consists of a hub and peripheral. The hub plugs into a central area of the older person's home while a secondary peripheral is attached to their keys. These two products work together to track daily living patterns - identifying unusual changes in routing and alerting carers to immedate and potential health concerns via a mobile app, including sharp declines in health like worsening dementia or the early onset of flu. The project makes use of Eddy Labs' existing audio recognition technology, adapting it to provide daily routine monitoring for early detection of potential health problems.

Poor adherence to prescribed medication is known to be a major problem for all long-term conditions, with only 50% of medication taken correctly. Non-adherence in the NHS is estimated to cost more than £500m per annum and is associated with a 50% increase in falls. This project will add sensors to existing medication packaging so that friends, family, service providers and healthcare professionals can remotely monitor medication consumption and assist the elderly person with adherence. Unique aspects of the project are a sensor design that can be added to weekly medication trays at minimal incremental cost with no change to current pharmacy procedures and communications technology that can be easily self-installed in every home.

Ostom-i Alert is a sensor that clips onto any ostomy bag and sends Bluetooth alerts to an app on a patient's mobile device telling them when their bag is filling. Currently patients with stoma bags have no warning when their bags are filling. This results in overflows and spills, particularly at night. The incidents are distressing, embarrassing and reduce their quality of life and lead to additional health conditions including infections. This device allows patients to set personalised alerts for their bag. The device also captures useful information on volume of output which can be emailed to patient and clinicians.