| | June 2019 19At long last, the business adoption of Internet of Things (IoT) is picking up steam and entering mainstream production, initially improving existing processes and operations. Companies across industries are moving away from pilot projects and proofs-of-concept and are beginning to run their businesses on IoT. But, we are not out of the woods just yet. Challenges such as existing business structures, organizational cultures, legacy system integrations, fragmented standards and security are hindering IoT from reaching its full potential.To flourish, IoT needs a supporting cast of technologies --from analytics to blockchain--as well as an industry-wide shift to open standards, which allow these technologies to interoperate. First, let's take a closer look at the key emerging technologies required for IoT success.The "secret sauce" of IoT, analytics and artificial intelligence (AI) allow for the real-time processing of data in motion, rather than traditional centralized batch analytics. In many ways, AI is the brain and IoT is the body: IoT is both the source of real-time data for AI applications, and the means of executing AI decisions. Although many IoT AI applications are still in the proof-of-concept stage, AI is already transforming many production applications, serving as the backbone of predictive analytics and predictive maintenance capabilities.Our next technology category is cloud/fog computing. The "Cloud Fog Continuum" is where data analytics does most of its work. Traditionally, batch analytics took place in the cloud, but fog computing extends cloud capabilities in the areas such as networking, computing and storage, and functional safety to the edge of the network, where the data is generated. To conserve bandwidth and ensure real-time data processing, fog nodes sort through mounds of data and send only exceptions back to the cloud for further analysis. In cases where latency is a challenge, fog nodes can send real-time alerts, allowing users to take immediate action. AI systems are moving in this direction as well. Once the logic is set, AI systems can run in specialized fog notes using a field-programmable gate array (FPGA), or even an application-specific integrated circuit (ASIC). Such integrated, policy-based cloud to the edge systems will lower costs and support greater adoption of driverless vehicles and other real-time AI solutions.IoT security technologies and strategies are also vital to success. Today, all major vendors are investing in IoT security alongside other security domains, and security companies and industry groups are accelerating work on standards, interoperability, certification and security education. Additionally, businesses are moving from "security by obscurity" into comprehensive policy-based security architectures managed by the chief security officer teams. These must be built into every part of IoT operations, focusing on preventing security breaches, identifying hacking attempts and remediating problems. One specific technology enabling IoT is blockchain, which allows for a secure exchange of value between entities in distributed networks. Blockchain creates a tamper-proof record of transactions, making it ideal for tracing the source of goods throughout production and distribution. Bitcoin is perhaps the most famous application of blockchain technology; THE STATE OF THE INTERNET OF THINGS (IOT): HOW EMERGING TECHNOLOGIES AND OPEN STANDARDS WILL ACCELERATE THE INDUSTRYBy Maciej Kranz, VP Corporate Strategic Innovation Group, CiscoSTARTUP INSIDERTo flourish, IoT needs a supporting cast of technologies--from analytics to blockchain--as well as an industry-wide shift to open standards, which allow these technologies to interoperate
< Page 9 | Page 11 >