Very rarely does a technology come along that makes engineers completely rethink product development. Generative design is one such innovation and it is propelling the manufacturing industry into an entirely new realm. Combined with Augmented Reality (AR), the possibilities are limitless.
The modern manufacturer has a plethora of advanced technology options to choose from. For example, mobile robots can streamline assembly line processes and simulation software can shape the product or process design. Although the COVID-19 pandemic may have put a hold on heavy investment from some companies, the hiatus was just temporary. Whether it’s pressure from the competition, workplace safety, government regulation, or something else entirely, manufacturers have been and will continue to be one of the most significant market opportunities for technology vendors.
Investors and shareholders are increasingly losing their patience with telcos, which have promised that their enterprise revenue will soon overtake their consumer business. At the same time, enterprise end users are not yet convinced that today’s 5G can address their pressing key pain points in line with the IMT-2020 vision most 5G suppliers are preaching.
Augmented Reality (AR) has an important role to play in the modern and future workplace—remote assistance, training, workflow guidance, and knowledge capture can all be realized with AR deployment. However, integrating AR into existing platforms has proven to be a formidable challenge to early adopters because of the complexity of Information Technology (IT) and Operational Technology (OT) cohesion. Ultimately, Return on Investment (ROI) from AR technologies will be heavily dependent on how seamless the integration process is.
Machine Learning (ML) is increasingly being integrated into edge computing solutions. ML at the edge improves the user experience via latency reduction, near-real-time data analysis, privacy, and security. Vendors are stepping up to the plate to provide services and platforms that streamline processes and reduce the time to market. In this post, you'll read about five examples of edge ML to better conceptualize this helpful combination.
According to ABI Research forecasts, the total installed base of devices with Artificial Intelligence will grow from 2.7 billion in 2019 to 4.5 billion in 2024. Billions of petabytes of data flow through AI devices every day. However, right now, most of these AI devices are working independently of one another. Yet, as the volume of data flowing through these devices increases in the coming years, technology companies and implementers will take advantage of multimodal learning – and it is fast becoming one of the most exciting and potentially transformative fields of AI.
With smart home applications becoming ever-more popular, and with households making heavy use of streaming multimedia services, the growing demand for reliable, high-capacity home networking technology shows no sign of slowing down. As a result, Wi-Fi, which has been the dominant player in the home network market for years, may be facing some competition from two wired networks: G.hn and Multimedia over Coax Alliance (MoCA) 2.5.
The benefits of Advanced Metering Infrastructure (AMI) are undeniable, as it leverages technologies like smart meters to provide real-time, or near real-time, two-way communication of information and energy levels between utility companies and Internet of Things (IoT) devices. This provides a more transparent snapshot of an energy grid. Cybersecurity challenges in smart grids are a prevalent threat to the governments and privately-owned organizations replacing traditional energy infrastructure.
When it comes to the robotics market, automation-enabling devices like cobots and 5G robots tend to garner a lion’s share of the attention. However, there is one technology that has flown under the radar yet is poised to make just as big of an impact – exoskeletons. By 2030, global revenues will reach more than US$3.9 billion in this emerging market, with industrial use cases being a major catalyst.
Forecasting where exactly the Electric Vehicle (EV) supply chain is going is a nearly impossible endeavor, with a wide range of unpredictable factors to consider, such as fuel prices, attitudes toward green energy, government policies, availability of charging stations, vehicle range, and vehicle affordability. One thing that can be concluded is that Original Equipment Manufacturers (OEMs) are going to focus on providing flexibility to consumers in order to gain market share. But the rapid development of so many new car models will place a tremendous amount of pressure on ecosystem partners that can’t meet demand in such a short time span, resulting in inevitable issues with the EV supply chain.
