Incontinence is the inability to control one's urine or bowel movements, it's most common among older people, those with dementia, and other faculty diminishing conditions; it is also a major driving force in long-term care admissions (Tariq 2004). At least half of the elderly population within Irelands, Britain's and North America's care homes (CH) suffer from incontinence. To this end, Connected Health and Arrow Electronics have developed an innovative and patented non-invasive incontinence monitor, called airCeption. Uniquely airCeption boasts the ability to be a remote and fully no-contact device. airCeption scans the ambient air surrounding an incontinent sufferer, searching for wetting or soiling episodes. Upon detection, airCeption transmits an alert to a dedicated member of staff allowing a prompt and well-managed care response. Being a remote healthcare offering, all the relevant technical compliance guidelines are adhered to, including, GDPR, HIPPA, ENISA, CoP & Azure Best Practice, as well as having FCC + CE(ETSI) pre-scan checks passed. The goal now is to fully validate the technology across relevant healthcare sectors, which include, though not limited to, Hosptial Care, Nursing-home Care, EMI Care, Domiciliary/Home Care, Hospice Care, Neonatal Care. Additionally, the applicants proprietary mobile and web applications not only alert carers to incontinent events, though too, enables the carers, to apply bristol stool chart inputs. With these confirmation inputs and event details being recorded, in the cloud, the applicants have started working with the Microsoft Insiders Labs to apply machine learning to their technology, with the view to improve performance and to start looking at other relevant insights that may be generated e.g via toileting windows to promote continence, urinary tract infection via frequent UIs, constipation etc. Having such insights readily available may provide an entirely new measure around incontinence care. With this, this project will lead to the development of 100 fully accredited units, for test deployment through all applicable healthcare sectors. These test demonstrations will allow a complete analysis of the technology performance, provide deep insights into practical matters such as cloud costs, user feedback etc all of which will validate the offering and allow for any small alterations. Furthermore and importantly the volume of units will be required to start providing a large enough data set to determine the feasibility of implementing machine learning, which will be required for the implementation of continence promotion features.