In many parts of Asia, seasonal torrential rains bring with them floods that damage property and livelihood of citizens. Whereas in the past, city administrations, citizens and businesses can do almost nothing but ride out the unwelcoming waves of flood water and the potential diseases these carry, technologies like the Internet of Things (IoT), machine learning (ML) and artificial intelligence (AI) may provide respite for more forward-looking leaders. This is the case of the DKI Jakarta Provincial Government's Flood Control System in the Jakarta Smart City application. Developed by Jakarta Smart City in collaboration with the Jakarta Water Resource Service (DSDA) to optimise flood risk management in Jakarta, the project involved the use of IoT, AI and ML as part of an early warning system against the risk of floods in the city. As more organisations deploy IoT in commercial and industrial environments, the amount of data that is derived from these devices and sensors may prove important in improving quality, operational efficiency, and in the case of Jakarta – saving lives and property from natural disasters.

In the fight to stay competitive, manufacturers will look to AI technologies to fuel a successful operational transformation. With industry 4.0 in full force, manufacturers are pressured to stay competitive. Over the past year, there has been a massive industry-wide shift in the adoption of AI technology to keep up with the demand from customers. We've already seen one-third of IT professionals surveyed globally say their business is now using AI, with 43% saying their company accelerated their AI rollout. By utilizing AI, manufacturers can achieve greater operational efficiency and resilience – while generating cost savings and aiding customer growth, retention, and acquisition.

Sponsored Feature Internet connectivity has changed everything, including old-school industrial environments. It's a situation that's creating clear and present security concerns, and the industry needs new approaches to dealing with them. Industrial Internet of Things (IIoT) adoption is speeding ahead. Research from Inmarsat found that 77 per cent of organisations surveyed have fully deployed at least one IIoT project, with 41 per cent of them having done so between the second quarters of 2020 and 2021. The same research also warned that security was a primary concern for companies embarking on IIoT deployments, with 54 per cent of respondents complaining that it stopped them using their data effectively.

For decades, information technology (IT) and operational technology (OT) systems have co-existed in process industry enterprises, often with very little crossover or cooperation between them. Traditionally, OT has kept the plant running with proprietary, mission critical systems designed to meet key requirements for availability and uptime. Meanwhile, IT managed business applications from the front office and is traditionally responsible for computers and networks on an enterprise-wide basis. With the need to reduce cost and increase scalability, the IT and consumer worlds have been steadily trending towards open architecture since the 1980s, with expanding prevalence of open operating systems, programming tools, and hardware architectures. While OT adopted open technologies on a limited basis, for the most part it has continued to rely on manufacturer-proprietary controllers, networks, and application software. The rise of the Industrial Internet of Things (IIoT) and related technologies have greatly impacted IT and OT.

It's one thing to have sensors, it's another to extract value from them. As businesses across all sectors take their first steps toward Industrial IoT and edge computing solutions, extracting machine/sensor data and making it available for things like predictive maintenance and condition-based monitoring can prove challenging. The gap between OT and IT is widest at the edge – factories, oil rigs, wind farms, water treatment plants and more. In this webinar, we'll explain how an IIoT edge hub bridges the gap by collecting, parsing and storing machine/sensor data, and making it accessible via standard protocols such as MQTT and SQL – all without the need to write a single line of code. If you have already registered, click here to access.

Steve Durbin is Chief Executive of Information Security Forum. He is a frequent speaker on the Board's role in cybersecurity and technology. A technology-led revolution, dubbed Industry 4.0, is gathering pace in the industrial world where traditional processes and legacy technologies are being replaced by smart devices, automated machines and advanced forms of computing. The rise of Cyber Physical Systems (CPS), owing to exponential growth in technologies like the Internet of Things (IoT), artificial intelligence (AI), cloud, robots, drones, sensors, etc., is helping manufacturers improve efficiencies, productivity and the autonomous operation of production lines. Businesses are pouring billions of dollars in AI and automation, and the Industrial IoT (IIoT) alone is set to become a $500 billion market by 2025.

A technology-led revolution, dubbed Industry 4.0, is gathering pace in the industrial world where traditional processes and legacy technologies are being replaced by smart devices, automated machines and advanced forms of computing. The rise of Cyber Physical Systems (CPS), owing to exponential growth in technologies like the Internet of Things (IoT), artificial intelligence (AI), cloud, robots, drones, sensors, etc., is helping manufacturers improve efficiencies, productivity and the autonomous operation of production lines. Businesses are pouring billions of dollars in AI and automation, and the Industrial IoT (IIoT) alone is set to become a $500 billion market by 2025. IT/OT convergence could spell disaster for industries. As smart factories and supply chains connect the production line to the outside world via IIoT, digitally connected industries are becoming increasingly appealing to cybercriminals, who now have the opportunity to hijack high-value targets.

One of the areas where Information Technology (IT) and Operational Technology (OT) teams are more closely collaborating is in machine learning applications. At the recent ARC Industry Forum conference in Orlando, Blair Fraser, with Emerson Impact Partner Lakeside Controls, presented in a session, IT/OT convergence, Machine Learning and IIoT enables predictive performance monitoring of Fermentation Process. The challenge this application was to solve was to improve batch performance and reliability in a fermentation process. It was a challenging application since the process response was non-linear and variable. Additionally, the application was for an industry requiring regulatory validation and the solution needed to be part of a validated system.