Processors keep shrinking and getting smarter. What are the implications of how IoT modules are integrating sensors and processors? What is the implication of new device design? Where does the edge give applications the most benefit?

There are so many IoT platforms available that easy to get lost. However, Open Source platforms have been integrated into most cloud systems. What makes a good open source platform? Are some opens source platforms better for some vertical applications than others? What are benefits and drawbacks of the major Open Source IoT Platforms?

Intelligent gateways bring the value of the cloud to solutions that require evaluation and analytics. Does the use of the gateways reduce the cost of cloud services? What applications can’t afford the delay in cloud processing? Do intelligent gateways reduce the cost and problem of legacy systems when implementing intelligent edge solutions?

Code is the core of the IoT. How do you evaluate Open Source? Does the volume of code matter? What about the developer community? Is the code actively being supported and modified? Is the code filling a need? What are the advantages over proprietary systems and the drawbacks?

We used to say the network is dumb, but as solutions such as Network APIs, SDN and NFV have shown, the network is rich with capabilities. When it comes to IoT, the smart network offers a variety of features such as security, and cost control. Who are the leaders in supporting IoT with intelligent connectivity?

The Intelligent IoT Cloud Cloud computing enables “As a Service” solutions that has given birth to many an IoT service. As more intelligence goes the edge the need is for a better balance to interfacing with the cloud. Microservices are being designed to bridge the gap. What interfaces are needed for success? Do companies feel they have to choose between the edge and cloud?

When it comes to IoT things must connect at the application level, MQTT, CoAP, Restful, Modbus, etc. are all being used in the open source community. How should they be evaluated? Do they have parameters that will work well with any network protocol? This session looks at how things talk beyond the use of network connections?

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?

The world is full of sources of data and processes to monitor. Luckily, the sensor market is rich with solutions. These solutions can be difficult to parse and choose, however, and can require custom development. In this session, the panelists will look at the devices in the field and which factors are critical to consider in the selection process.

OT has two simple rules. If it’s running leave it alone, if its not, get it running. Those two rules do not sound like innovation is welcome. Yet IoT is delivering on Industrial 4.0 by increasing the data coming from sensors and enabling the SoftPLCs. How does smart manufacturing take us beyond measuring uptime and bring us to a new level of efficiency and production?

The options for IoT connectivity are so numerous and complex as to confuse anyone. It’s hard to know what is what when looking at Bluetooth, CBRS, cellular, LPWA, Sigfox, Wi-Fi, Wi-Sun, Zigbee and the rest. For the uninitiated, these can seem like equivalent alternatives. In this discussion, we will examine different methods of distribution, management and transmission.

One for the earliest and most diverse IoT markets is asset tracking. Whether you are tracking scooters or construction cranes, the principles are the same. Know where your products are and know where they are going. What are features that every Asset Tracking system needs? What is different ways location can be detected? What innovation is occurring?

Managing suppliers and distributors requires a chain of trust to be established. Keeping track of pallets, rail cars, shipping containers, and trailers is one way to trust but verify. Today using the combination of block chain and IoT is another way to ensure transfers of ownership is complete. How is the technology changing the capabilities to deliver the goods?

Most of the IoT is deployed remotely, either out in the field or in difficult to reach areas, and often have a life cycle of 5 years or more. Devices therefore often need to be activated once they are in place, and remotely maintained. In addition, these Things need to be kept up to date with security patches and software improvements. This session will be about what happens during and after initially deploying IoT.

Lots of changes are taking place in the way buildings are connected and managed. LED lighting, HVAC systems, personal emergency response systems, and surveillance systems are part of the revolution. In addition, there are changes in connectivity that should be noted. Bluetooth 5, Wi-Fi 6 and Private LTE are all bringing better security and bandwidth. Where should a Facilities Manager Start? What improves operations? Do all these opportunities have an RoI? What are the benefits to the employees?

Analysts count more than 700 platforms currently active in the IoT industry, but not all of them are equal. There are platforms for device management, analytics, applications, billing, cloud and operations. Can these platforms can be bundled, or does it make sense to leave some functions separate? In this panel, we will try to reduce the confusion and provide some IoT Platform guidance.

Many cities have been known for their industries, but their history is remembered by their football team names (e.g. Green Bay Packers and the Pittsburgh Steelers). Is now the time for collaboration between the cities and industry? What are the synergies? How can the cities support IIoT? What can they do specifically with infrastructure to spur development?

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.

All these sensors being added to the information is making a big data lake. For a human, is this lake navigable? Can ML turn big data into useful data? How will machine learning give enterprises better insight? How does ML influence edge intelligence in industrial systems?

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?

As 5G continues to grow as a powerful enabler of technologies, the number of vertical-market use cases continues to increase and produce more practical applications, including robotics, artificial intelligence, machine learning and big data that will contribute to analytics. These IoT applications will all need different requirements in terms of data capacity, speed, latency, reliability, coverage, location accuracy, and, most importantly, security. In this session, we will address these challenges by examining the network benefits of 5G for the IoT, including deployment considerations, building management issues, and security. Specifically, we will focus on how 5G will change how we think about connectivity for facilities, enterprise, and industrial applications.

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.

For many companies industrial espionage is a real concern, for others the employees may bring in a virus accidentally. Regardless of the root cause, industrial manufacturers need to be prepared. While traditional networks were considered closed systems, today’s connected industrial capabilities must contend with brute force attacks. Hackers can use ML to support their attacks, so it’s clear that companies need to fight fire with fire. What security best practices will take us getting beyond identity and auditing?

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.

As a human being connected to Internet through Facebook, LinkedIn, Twitter and phone applications, an understanding of my lifestyle can be seen. Likewise, a digital twin can follow the physical reality of assets and products to produce an image of IoT systems. What are the use cases for digital twins? Are there concerns about how digital twins can be used?

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.