This panel discussion will kick off our show by looking to the future. We will discuss the possibility of self-aware IoT and what Intelligence really means with respect to IoT and how it can leverage data, analytics and machine learning.

Is the innovator’s dilemma playing out in the IoT industry? We have many companies that have been in the business of IoT before IoT was called IoT. We also have new entrants that are benefitting from VC’s unicorn investments. Hear about the competitive strategies in a market that is so dynamic.

IT and OT need to find common ground as the use of analytics, digital twins, and machine learning enable process innovation. What are we learning about IoT’s role in innovation? How does the growing intelligence transform operations and implementations across the industry?

Machines have helped humans do amazing things through control and communication. The addition of machine learning and rich analytics enables machines to make critical decisions without human interaction. What are the compelling requirements for humans to delegate processes to machines and what are the concerns?

What happens when Moore’s Law, Cooper’s Law and Metcalf’s Law converge? The answer is the edge gets intelligent and the network increases its capacity to transmit. Traditionally the goal has been to minimize the bandwidth use, but these goals may be a thing of the past. Find out how the ability to transmit more data faster, and process data closer to the edge changes the IoT’s use cases. Will legacy systems stay as is, or having it built, will new solutions take advantage of the dynamics?

Nowhere does IoT have more applications and stricter requirements that in the auto industry. With mapping technology enablement being integrated into GPS, driver assistance, entertainment and diagnostics, we have more sensors and computing being packed into a single space. With all the complexity, the industry sees their implementation as a competitive advantage. This panel looks for the best practices that the industry can agree upon to implement, and the innovation that keeps them apart.

When the concept of Smart Cities first took off some government funding became available for investing in solutions, that made the City the boss. Then various utilities started enabling solutions and the companies were driving decisions. How can smart cities be a win / win for enterprise and government? What are realistic goals to be made between the partners? Do smart cities have to have visible results for the politicians to have public support?

A politician is used to seeing poll numbers, but smart city solutions are not always visible to the public. The implementations of Smart Cities show a wide range of opportunity. How can analytics be used in a smart city? Do analytics make for better decisions? What are the metrics a Smart City should be judged by?

This spotlight session will explore the unique concerns in securing a Hyper-connected Smart City.

Most cities have centralized systems; the board of Ed, the Municipal services, the mayor’s office. The edge, on the other hand, is where the smart cities “things” are being deployed; street lighting, parking systems, schools. What are the implications for city IT departments to support edge solutions? Find out how the can the edge be integrated into existing systems and what new services are enabled by deploying at the edge.

A city is a font of useful and actionable data. To be a Smart City, municipalities must learn to capture and capitalize on that data. In this session, our panel will discuss the power and uses of Data and Analytics to make cities smarter.

As the edge becomes more intelligent, the communication strategy becomes one of enabling peers to share and react intelligently. These networks require additional design for security and analytics. What are the security risks? What are the advantages of near real-time collective analytics?

Security is the topic that everyone complains about, but no one listens to the solutions. This session is looking to change that by looking at the requirements. How can advances in machine learning change the capabilities of detection, command and control.

Being Smart is about more than access to and collection of Data. To truly reach Smart City status, municipalities must leverage analytics to make its volumes of data actionable and lead to improved operations and a happier, more invested citizenry.