Adopting AI and robotics in the social care industry

Open Access Government | April 26, 2019

Technology can help improve the social care industry in many ways, but there is still hesitancy towards adopting artificial intelligence (AI) and robotics. Matt Hancock has once again called for the NHS to adopt new technology in order to survive, as a new report by the Taxpayers Alliance suggests one-tenth of the NHS budget could be saved by automating more services.
As the population ages, the demand for high-quality carers rises. By 2026 it’s predicted that the UK will need around 420,000 more carers, but with the current vacancy rate high and the amount of those showing interest in the care sector diminishing, it’s important that technology is utilised in order to help fill the gaps and provide the best social care possible. IoT, AI, and robotics can all play a part in improving client care and carer well-being.
IoT sensors can unassumingly monitor movement, normal behaviours, humidity, and temperature across a home enabling a care organisation to rapidly gain a picture of each individual’s day to day routine – information that is then key to flagging changes which could reveal a problem.

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Virtual desktops offer centralized management, lower maintenance costs, improved security, and remote access to superior storage and computing capabilities. Historically, however, they were limited by the inability to handle the graphics-intensive computing needs of designers, engineers, and scientists. The graphics processing requirements of computer-aided technologies (CAx), limited graphics API support, and the inability to share physical GPUs all made it unfeasible to use virtual desktops as graphics workstations.

Spotlight

Virtual desktops offer centralized management, lower maintenance costs, improved security, and remote access to superior storage and computing capabilities. Historically, however, they were limited by the inability to handle the graphics-intensive computing needs of designers, engineers, and scientists. The graphics processing requirements of computer-aided technologies (CAx), limited graphics API support, and the inability to share physical GPUs all made it unfeasible to use virtual desktops as graphics workstations.

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