Juan Carlos Augusto, Philippe Lalanda, Massimo Mecella Intelligent Environments are populated with numerous devices and have multiple occupants, inherently exhibit increasingly intelligent behaviour, support consistent functionality and human-centric operation (humans, as opposed to mere users, have increased requirements from a system, including, for example, intuitive interaction, protection of privacy, fault-tolerance etc.), and provide optimized resource usage. The development of Intelligent Environments is considered the first and primary step towards the realization of the Ambient Intelligence vision and requires input from research and contributions from several scientific and engineering disciplines, including computer science, software engineering, artificial intelligence, architecture, social sciences, art and design. The series of IE conferences have been consistently creating a unique blend of researchers in these disciplines, fostering cross-disciplinary discussions, debate and collaborations.

In 2016, Columbus, Ohio, beat out 77 other small and midsize US cities for a pot of $50 million that was meant to reshape its future. The Department of Transportation's Smart City Challenge was the first competition of its kind, conceived as a down payment to jump-start one city's adaptation to the new technologies that were suddenly everywhere. Ride-hail companies like Uber and Lyft were ascendant, car-sharing companies like Car2Go were raising their national profile, and autonomous vehicles seemed to be right around the corner. "Our proposed approach is revolutionary," the city wrote in its winning grant proposal, which pledged to focus on projects to help the city's most underserved neighborhoods. It laid out plans to experiment with Wi-Fi-enabled kiosks to help residents plan trips, apps to pay bus and ride-hail fares and find parking spots, autonomous shuttles, and sensor-connected trucks.

What is Industry 4.0 and Industrial IoT? Industry 4.0, Industrial IoT, and Industrial Internet are used interchangeably when talking about the new era of manufacturing. A digital ecosystem of connected machines, equipment and devices that communicate with one another, this cyber physical system with machine-to-machine (M2M) communication monitors and evaluates the physical processes in a manufacturing facility to ultimately make decentralized decisions. An evolution from Automation & Robotics, Industry 4.0 is the combination of computers and machine learning algorithms that gives equipment the ability to adjust and control processes based on data it collects. This is all done with very little human intervention.

Smart homes are one of those technology ideas that never seem to catch on, despite the efforts of technology heavyweights like Amazon and Google parent Alphabet. Could Roomba, the popular robotic vacuum cleaner, be the missing link that finally makes home automation useful and convenient?

Industrial Internet of Things (IIoT) is already revolutionizing domains such as manufacturing, automobiles and healthcare. But the real value of IIoT will be realized only when Machine Learning (ML) is applied to the sensor data. This article attempts to highlight how ML augments IIoT solutions by bringing intelligent insights. Cloud computing has been the biggest enabler of connected devices and enterprise IoT. Cheaper storage combined with ample computing power is the key driver behind the rise of IIoT.

The data volumes expected from the Internet of Things (IoT) are certain to be large – too large, in fact, for even an army of trained analysts to turn into useful information in a reasonable amount of time. This is why every solution aimed at the IoT relies heavily on automation, simply to manage the flow of information between devices and to centralized storage and analytics systems. But even this is not likely to be enough. To fully leverage the IoT, it's becoming obvious that the enterprise will have to utilize new forms of artificial intelligence and machine learning to basically allow the environment to makes its own use of available data and tell human operators what needs to be done. Already, this is emerging on leading IoT platforms.

When it comes to public cloud-based IoT platforms, Amazon and Microsoft have fierce competition from an unexpected corner – IBM. While the company hasn't seen much traction with SoftLayer (IaaS), and Bluemix (PaaS), it's upping the ante on IoT and Cognitive Computing. IBM Watson is slowly but steadily gaining customer adoption. From Visa to BMW to Bosch to Kone, Watson now boasts of some impressive partnerships. IBM recently hosted a two-day briefing at its newly minted IoT facility in Munich.