IoT is trending. Companies invest in new tech...
What trends will be shaping the Internet of Things business solutions landscape in the following year?
The Internet of Things Trends for 2019
The Rise of Ethical IoTAccording to Gartner, the global IoT device park will grow up to 14.2 billion units in 2019. As more processes that previously required human assistance become partially or fully automated, cutting-edge IoT deployments should be both fault-free and socially acceptable. A lot of issues regarding enterprise-scale IoT implementations such as data ownership and privacy, as well as algorithmic bias, should be clarified. Through 2019, more organizations are expected to form IoT ethical councils to reimagine corporate IT strategies, educate employees and secure data through regular device audit and firmware updates.
Antonio Grasso, CEO at Digital Business Innovation and a recognized IoT and Digital Transformation expert, lays special stress on the need to develop and employ the “continuous update” IoT security strategy, since most connected systems have direct access to mission-critical data and work autonomously. In order to reduce the expenses associated with scanning device repositories, identifying the gadgets pending an update and upgrading firmware on a case-by-case basis, more companies are expected to streamline embedded software updates using cloud-based services and the dynamic groups/continuous jobs technology or bulletproof IoT solutions at the microcontroller level. The blockchain-enabled IoT deployments and smart contracts can also contribute to the Internet of Things’ overall security and integrity.
Stronger Emphasis on IoT UXWith ubiquitous automation, screen size diversity and the distribution of functionality across devices with different capabilities which, among other things, use different communication protocols, the Internet of Things has changed the way companies and individuals interact with technology, and the standards of IoT user to device mapping are still being defined.
As of now, many connected products require manual configuration, which contradicts the essential principle of IoT — that is, the elimination of human-to-computer interactions.Although the voice recognition technology is getting considerable traction (especially in the Smart Home domain), we won’t step into the configuration-less IoT era without virtual assistants with more advanced cognitive capabilities.
According to Alexandra Deschamps-Sonsino, the author of Smarter Homes: How Technology will Change Your Home Life, there are multiple barriers to integrating speech recognition software into connected home solutions, let alone multi-tier enterprise IoT solutions orchestrating equipment and security systems. These include “seemingly helpful audio prompts based on in-home behavior”, “weird concepts of trust” (one cannot entrust a voice assistant with a seemingly simple task — for example, booking a flight or an appointment with a doctor — without double-checking it) and inadequate situational awareness (you can hardly expect Alexa to intervene in emergency situations unless a proper command is issued).This calls for the development and implementation of AI-based data processing solutions on the infrastructure level, as well as increased synchronization of connected systems.
Further Development of IoT Analytics SolutionsGreater adoption of connected solutions in business translates into the growing amount of data on device usage and performance, as well as environmental conditions in which IoT systems operate. Nevertheless, recent studies show that only 1% of IoT-generated data is analyzed and acted upon.
Applying Machine Learning to sensor data can give companies a better understanding of both connected products and their interactions. This, as we mentioned previously, necessitates a brand-new approach to IoT infrastructure development on the back-end and device level.Our very special guest Avrohom Gottheil, a top-ranked IoT expert and founder of #AskTheCEO, an online education platform where CEOs and technology experts share their thoughts on Digital Transformation, believes Cognitive IoT will be the most important Internet of Things trend in 2019 and beyond.
According to Mr. Gottheil, “With industry analysts predicting over 50 billion IoT devices within the next few years, companies and government authorities are going to have real-time access to massive streams of data, the likes of which we never thought possible. It will be virtually impossible for humans alone to process this amount of data in any sort of meaningful manner. AI will no longer be a “nice to have,” but mission critical for businesses to remain competitive. Integrating AI into your company’s digitization strategy gives access to actionable insights from the new data deluge, not just the data from cloud-connected software, services, chatbots, and devices, but ALL online data sources globally — simultaneously and instantaneously. This superhero-like capability creates the opportunity for you to program autonomous, decision-making capabilities into your workflows.”Therefore it can be concluded that cloud companies which provide Machine Learning as a Service (MLaaS) solutions via APIs will continue to flourish in the IoT analytics era. As cloud computing starts to show its limits stemming from high server costs and connectivity issues, however, more tech-savvy enterprises will partially relocate data storage and processing solutions closer to IoT devices. Some of the early examples of self-sufficient IoT systems with advanced cognitive capabilities include connected traffic and surveillance cameras which detect pedestrian and automotive traffic patterns and predictive maintenance solutions implemented by manufacturing and utilities companies. It should be noted, nonetheless, that heavy computing operations cannot be performed at most endpoints, so the data generated by devices has to be matched against AI models implemented on the infrastructure level.
Emergence of Predictive Digital TwinsAlthough Digital Twins — i.e., digital replicas of a company’s assets which enable real-time data acquisition, visualization and analytics — have long been on Gartner’s and Forrester’s A lists, the leading-edge technology struggled to make a significant contribution to IoT development, particularly in the realm of the Industrial Internet of Things. The lack of sensor data processing solutions and legacy IT systems are still considered one of the major obstacles to Digital Twins’ large-scale implementation. Furthermore, the application scope of Digital Twin solutions utilized by GE, Kaeser, Stara and other technology pioneers is currently limited to equipment performance monitoring based on sensor readings.
Next year and beyond, more enterprises are expected to invest in predictive Digital Twins powered by Machine Learning which allow decision makers to model processes prior to the implementation of novel technology solutions, with AI algorithms acting as virtual sensors.
IoT in 2019: from Data Deluge to Data-driven InsightsDigital Transformation is reshaping industries. With 86% of enterprises planning to increase investments in IoT development through 2019, it’s fair to say every company is a technology company these days.
With technology, however, comes responsibility — along with vast amount of structured and unstructured data generated from connected equipment and employees which has to be collected, processed and acted upon.Although 94% of companies that implement connected solutions to streamline business processes and increase productivity register steady returns on their IoT investments, the future of enterprise IoT depends on intelligent data processing — and 2019 might be the turning point for both software vendors and their customers.