LG has placed its trust on Google Assistant and has given it the power to control its smart appliances. While it teamed up with Amazon earlier this year to give its refrigerators built-in access to Alexa, its partnership with Google is much bigger in scale. Now, you can control any of the company's 87 WiFi-connected smart home appliances by barking out orders through a Google Home speaker or through a compatible iOS or Android smartphone. Once you're done setting voice control up through LG's SmartThinQ app, you can use commands within a Home speaker's range or through a phone to tell your fridge to make more ice or to tell your AC to adjust the temperature. If you have an LG washing machine, you can ask Assistant how much time is still left before your load is done.
Whirlpool's smart appliances have already had some voice assistant control, but they're about become particularly AI-savvy. The company has unveiled a 2018 lineup where many appliances support both Amazon Alexa and Google Assistant, letting you control most of your home using the smart speaker (or mobile app) you prefer. You can check the time left on the washing machine, start the dishwasher or change the temperature of your fridge without lifting a finger.
A self-locking mailbox could someday flag down delivery drones and intelligently screen your driveway for intruders. Columbus State University computer scientist Lydia Ray presented the technology, called the ADDSMART project, during a 20 October session at the annual IEEE Ubiquitous Computing, Electronics, and Mobile Communication Conference in New York City. The project aims to achieve two goals: clearly marking addresses for autonomous vehicles, and reducing the energy and data storage costs of home surveillance systems. An early prototype mailbox attachment suggests that the trick, in both cases, may be radio-frequency identification. Powered by an Arduino Yun processor, one component of the ADDSMART device controls a high-frequency 13.56-MHz RFID reader, USB camera, passive-infrared motion sensor, solenoid lock, and an onboard Wi-Fi module.
The most widely accepted defining feature of the semantic web is machine-usable content. By this definition, the semantic web is already manifest in shopping agents that automatically access and use web content to find the lowest air fares or book prices. However, where are the semantics? Most people regard the semantic web as a vision, not a reality -- so shopping agents should not "count." To use web content, machines need to know what to do when they encounter it, which, in turn, requires the machine to know what the content means (that is, its semantics). The challenge of developing the semantic web is how to put this knowledge into the machine. The manner in which it is done is at the heart of the confusion about the semantic web. The goal of this article is to clear up some of this confusion. I explain that shopping agents work in the complete absence of any explicit account of the semantics of web content because the meaning of the web content that the agents are expected to encounter can be determined by the human programmers who hardwire it into the web application software. I therefore regard shopping agents as a degenerate case of the semantic web. I note various shortcomings of this approach. I conclude by presenting some ideas about how the semantic web will likely evolve.