This year has been characterized by rapid changes in engineering technology and production. For example, wearables that used to only track the date, time, and a user’s steps can now monitor one’s blood pressure, sleep habits, and stress levels. This means devices, including smartphones, must provide real-time data on multiple variables whenever requested to be of value to consumers.
The demand for automation is also increasing — from automated coffeemakers and home alarm systems to industrial production lines in factories to “smart” cities with automated streetlights and intelligent energy systems. The electronic design engineer of today must continuously be updating and innovating to succeed in this competitive technology landscape. It’s no longer enough to be familiar with sensors or digitalization.
The speed at which technology is developing means many engineers must also understand the Internet-of-Things (IoT), virtual reality (VR), artificial intelligence (AI), robotics, cybersecurity measures, and more. To keep up, engineers must embrace change and continually update existing skills while learning new ones.
The Fourth Industrial Revolution — a term coined by Professor Klaus Schwab and presented at the World Economic Forum in 2016 — is truly here.
Industry 4.0 & automation
Factory automation presents new possibilities and challenges in the industrial environment. It involves the use of control systems, such as robots or computers, for process or material handling, with zero or little need for human intervention. Industrial robots can operate 24 hours a day, seven days a week, performing repeatable processes.
A recent report found that automation is going to take over the majority of factory and industrial production plants within the next three years. Benefits include increased productivity, typically a more precise or higher quality product, improved safety, and fewer repetitive tasks and sometimes even shorter work weeks for workers.
The majority of these systems can be greatly improved with the use of IoT and AI. For example, machine-to-machine (M2M) refers to direct communication between devices, typically using wireless communication and IoT.
Although there are concerns about automation and AI reducing the availability of jobs, human-to-machine (H2M) is still expected to occur — where humans interact with the devices and technology. Engineers will still be required for system updates, reprogramming, and new design processes.
One other challenge when implementing automation is the cost of such programs, which may include automated robots for production lines. Ideally, the long-term production payoff is worth the initial expenses.
5G connectivity
Engineers are wise to keep up with 5G developments. According to analyst firm Gartner, 20.4 billion “coherent things” are going to be in global use by 2020 and the fifth generation of connectivity will strongly support that.
5G connectivity is expected to provide greater data rates, less latency, and much quicker downloads. Experts predict that it will affect everything from the factory production line by enhancing M2M connectivity, to smart cities and the way people work, live, and interact with people — and their connected devices. Overall, 5G is better able to handle multiple, and even thousands, of devices simultaneously.
To work efficiently and reliable, IoT requires strong sensors and fast network speeds. Essentially, 5G means the technologies that depend on IoT are going to be able to work at a much faster pace. It also means that automation and VR will be able to support more capabilities and enhanced user experiences.
This is because user immersion in virtual reality is essential. Any network latencies will affect the authenticity and quality of the experience.
5G is also expected to transform healthcare by, for example, supporting remote patient monitoring, advanced imaging equipment (and more quickly transferring large files, such as X-rays or MRI results), and better or quicker patient diagnosis.
Cybersecurity
With advances in 5G and IoT, security should be a major concern for tech companies. Analysts have predicted that IoT is going to generate new security risks for enterprises and consumers.
Cybersecurity research and learning to stay ahead of the competition before vulnerabilities turn into serious breaches are critical. This means designing systems that can proactively monitor and predict cyberattacks. One way to do so is by implementing AI and machine learning (ML) tools.
Cybersecurity engineers are also necessary to program such systems, and properly monitor risk and threat assessments during product development — ensuring that security is a dominant feature of every product and device.
The Fourth Industrial Revolution is leading to major technology changes in terms of speed, scale, and might, unlike anything previously experienced. It’s important to be prepared.
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