In terms of the smart home, ambient intelligent devices quietly pay attention to the actions of end users in certain environments—learning what people do, how they respond, and their interests—to make intuitive and data-based guesses regarding what users want and which action to perform.
These can be as simple as turning on a light or making sure your home is pre-heated in the evening because it knows you arrive home late on Tuesday nights. Ambient Intelligence (AmI) represents one of the more advanced, almost esoteric, elements in smart home development.
It offers a new level of human-computer interaction in which people are surrounded by intelligent and intuitive interfaces embedded in the everyday objects around them. AmI, by extension, is a key element in smart environments, smart networked objects, augmented and mixed realities, intelligent interfaces, and wearable computing, to name a few.
While it's gradually being incorporated, other issues related to Smart Homes still need to be worked out, including standardization, accessibility, and affordability.
Ambient Intelligence and the Smart Home
AmI combines the connectivity of the Internet of Everything (embedded sensors, wireless technology) with the information intelligence of big data analytics and the ubiquity of smart devices (smartphones, tablets, wearables).
The possibilities for smart home technology that make it truly compelling to consumers rely on a number of moving parts. Some of these include:
- Sensors: Tiny, inexpensive beacons that incorporate Bluetooth Low Energy (BLE) to transmit signals as part of a smart home platform
- Standardization: The ease, or lack thereof, with which proprietary home devices work together
- Ambient Intelligence (AmI): AmI weaves together data from many sources to "learn" user's habits, understand the context and purpose of a request, then perform an action
- Wireless Communications: Mobile, Wi-Fi, Bluetooth and energy-saving communication protocols enable anytime/anywhere connectivity
- Human-Computer Interaction (HCI): The capacity of intelligent, intuitive interfaces embedded in everyday objects to respond to end
According to a study by GMSA Intelligence, by 2020 smartphone users will comprise 70 percent of the world's population. In addition to direct access to the Internet, and functioning as key control devices for the smart home, smartphones contain a wealth of useful information, such as geolocation, app logs, and data important to achieving accuracy for AmI.
Increasingly, established players and startups are devoting resources to capitalizing on that data and developing capabilities for virtual assistants, tangentially related to AmI.
Toward that end, Google recently purchased DeepMind Technologies, an AmI company focused on getting computers to learn in ways similar to the human brain. In general, deep learning systems create networks of artificial neurons that share information with each other and build on that knowledge.
Creating smarter artificial intelligence requires weaving together data from diverse sources to understand the context and purpose of a request. AmI goes hand-in-hand with the goal of virtual assistants, including Apple's Siri, its more complex alter-ego, Viv, and Kimera's Nigel.
One version of AmI for the smart home would consist of, for example, smart refrigerators that connect to a personal cloud and store data on groceries. A combination of software, connections to the fridge manufacturer and an ISP would then enable grocery ordering, tracking, and payments.
Smart Homes in the Real World
A key smart home challenge is the accurate tracking and instant, automatic response to individuals as they move through an environment. Several factors are converging to make smart home interactivity a reality.
For example, the widespread deployment of wireless capabilities—mobile, WiFi, Bluetooth—enable communication from just about anywhere. But tracking is a simple concept that is much harder to execute.
That's because instant smart home interactions require the processing of locational data and the use of efficient algorithms. (It's striking how a few seconds delay can matter when simply turning on a light.)
This is partly related to the difficulty of Bluetooth beacons, or sensors, to effectively relay location, and the speed with which current algorithms can process and respond to the information.
What's Next For the Smart Home?
The current smart home market is not only diffuse with competing visions, it's also hampered by interoperability issues and an overall lack of standardization.
Industry watchers and analysts believe the key to the success of the market hinges less on a particular device and more on the connectivity platform all of the major players agree to buy into. The value is in increased simplicity, not more complexity.
For example, the notion of employing six different apps to automate a single home is deeply unappealing to consumers. As AmI systems for the smart home become more affordable and accessible, and are better able to respond to home owners' needs, look for the next critical issue—privacy.
In this regard, effective security will be crucial, both to protect information and to guard against the potential abuse of those systems.
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