Next-gen electric radiators powered by waste heat
CategoriesSustainable News

Next-gen electric radiators powered by waste heat

Spotted: Data centres are a significant but often overlooked contributor to climate change, responsible – along with their accompanying data transmission networks – for around one per cent of global greenhouse gas emissions. Computer processes generate a lot of heat as a by-product, and cooling systems therefore account for a significant proportion of the energy consumption of a typical data centre.

Now, however, French startup Hestiia is looking at the heat generated by computing differently, using it to create a new kind of domestic radiator, called the myEko.

The startup collects and upgrades used ASIC chips from data centres and places them on a custom-made electronics board, which forms the core of the radiator. Conductive layers and piping then transfer the heat produced when the refurbished chips perform calculations to the space that needs heating.

Hestiia provides the compute capacity embodied in the radiators to companies that need it for heavy workloads such as scientific research, 3D modelling, crypto mining, and blockchain. The startup’s customers, meanwhile, install the radiators to heat their homes.

In addition to being highly efficient, the radiators use smart sensors to automatically regulate the temperature of a room, and users can tweak preferences on the app, such as setting day and night modes to automatically adjust temperatures for each space depending on the time of day. And, the system further detects temperature changes from actions such as opening a window and alerts owners, signalling them to turn the temperature down to avoid wasted energy. In ‘geolocation mode’, the system can detect when a user is coming home and turn on the heating accordingly.

Hestiia’s initial product was a water heater system called SATO that similarly reused the heat from computer chips to supplement a standard boiler. The startup is now pivoting to focus on myEko, which it believes is an even more accessible, mass-market solution.

Other innovations in Springwise’s library working to decarbonise computing include a new power distribution unit that maximises efficiency, and the use of AI to reduce the number of calculations required.

Written By: Keely Khoury and Matthew Hempstead

Reference

Next-gen care: AI spots early signs of health decline
CategoriesSustainable News

Next-gen care: AI spots early signs of health decline

Spotted: An ageing population, combined with the potential growth of dementia, is contributing to the immense pressure being put on the UK’s National Health Service (NHS). Part of the challenge lies in the high numbers of vulnerable people admitted to A&E, who are then kept in hospital while a suitable care home is found, or homecare support is organised.  

Remote monitoring technologies help care teams quickly respond to emergencies and often provide a life-saving service. Physiotherapist Louise Rogerson and data scientist Jonathan Burr wanted to find a way to prevent some of those emergency admissions by deploying smart home care earlier and in more detail. The co-founders built Howz, a smart home care monitoring system that works to prevent falls and other injuries by identifying slight changes in a patient’s behaviour.  

Using artificial intelligence (AI), a motion sensor, smart plug, door sensor, and hub, Howz’s package helps carers track energy use and at-home movements. The AI quickly establishes a base routine for each patient and uses that information to identify early behavioural changes and capability that indicate a possible need for social care support. Those early alerts – such as no electric kettle use that day – help social care teams and family carers spot and react to small changes that may otherwise go unseen with current home care monitoring systems, before a more serious accident can occur.  

It takes only minutes to install the Howz system and data is available instantly via the app for individual carers and healthcare professionals. Howz provides round-the-clock monitoring and a care dashboard for those in charge of multiple patients. At the same time, privacy is an essential part of the system. No personal data is collected, and the main account holder can add or delete permissions for those using the app. Results show that the use of Howz reduces emergency admissions by 32 per cent and the risk of care home admission by 42 per cent. 

From Parkinson’s to mental health, Springwise’s library includes a variety of innovations using AI to provide customised, timely healthcare interventions.

Written By: Keely Khoury

Reference