According to Emerson, makers of this UP500W Sensi Wi-Fi Programmable Thermostat, their customers save up to 33% in energy costs every year using programmed heating and cooling schedules. The Sensi thermostat makes it easy to remotely control and schedule the comfort of your home using your phone, tablet or PC. You can start with a preloaded schedule that reflects common daily patterns and quickly adapt it to your unique schedule, or you can use the intuitive swipe controls to build a customized daily schedule in seconds. When your schedule changes, the app gives you continuous control to make adjustments, from across the room or across the world. And because it doesn't require a "C-wire" in most applications, Sensi works with most heating and cooling systems in the US and Canada.
Scientists in Toronto are developing an artificial intelligence system that would help people with Alzheimer's disease or other cognitive impairments live safely at home. The Toronto Rehabilitation Institute is working with University of Toronto researchers to make home-based computer systems that would assist elderly people with memory loss in living independently. More than 750,000 Canadians will have Alzheimer's or a related dementia by 2031, according to the researchers. "Often when a person gets moderate to severe levels of impairment, they are taken out of their home and put into a care facility," lead scientist Alex Mihailidis said in a written statement. "We are using artificial intelligence to support aging-in-place so that people can remain in their homes for as long as possible."
Z Advanced Computing, Inc. (ZAC), the pioneer startup on Explainable-AI (Artificial Intelligence) (XAI), is developing its Smart Home product line through a paid-pilot for Smart Appliances for BSH Home Appliances (a subsidiary of the Bosch Group, originally a joint venture between Bosch and Siemens), the largest manufacturer of home appliances in Europe and one of the largest in the world. ZAC just successfully finished its Phase 1 of the pilot program. "Our cognitive-based algorithm is more robust, resilient, consistent, and reproducible, with a higher accuracy, than Convolutional Neural Nets or GANs, which others are using now. It also requires much smaller number of training samples, compared to CNNs, which is a huge advantage," said Dr. Saied Tadayon, CTO of ZAC. "We did the entire work on a regular laptop, for both training and recognition, without any dedicated GPU. So, our computing requirement is much smaller than a typical Neural Net, which requires a dedicated GPU," continued Dr. Bijan Tadayon, CEO of ZAC.
Researchers have devised a new malware attack against industrial programmable logic controllers (PLCs) that takes advantage of architectural shortcomings in microprocessors and bypasses current detection mechanisms. The attack changes the configuration of the input/output pins that make up the interface used by PLCs to communicate with other devices such as sensors, valves, and motors. PLCs are specialized embedded computers used to control and monitor physical processes in factories, power stations, gas refineries, public utilities, and other industrial installations. The attack, which will be presented at the Black Hat Europe security conference in London on Thursday, was developed by Ali Abbasi, a doctoral candidate in the distributed and embedded system security group at the University of Twente in the Netherlands, and Majid Hashemi, a research and development engineer at Quarkslab, a Paris-based cybersecurity company. One version of the I/O attack is called pin configuration and involves the use of malicious code that switches an I/O pin's configuration from output to input, or the other way around, without the PLC's OS or programs knowing.