Experts Predict Industrial IoT Will Fuel Robotics Growth
The International Federation of Robots and Loup Ventures recently predicted that by 2025, overall robotics spending will increase to $13 billion, reports Business Insider. By that time, collaborative robotics sales, powered by the industrial Internet of Things (IoT), will grow from their current 3 percent market share to comprise over one-third of total robots sold.
According to Business Insider, most robots in manufacturing settings are stationary on the assembly line, perform routine jobs and leave complex tasks to their human counterparts. Over the next eight years, however, more sophisticated sensor networks, the growth of edge computing and the maturation of cognitive computing — combined with significant economic pressures from rising manufacturing wages — could launch a new generation of collaborative robots that can interact with people, complete ad hoc tasks and adapt to new scenarios.
Making Interactive Robotics Possible
According to Morgan Stanley, the best use case for industrial IoT and robotics is enabling remote diagnosis and the repair of stationary robots. Manufacturers are also highly interested in advancing collaborative robotics to create machines that interact with other machines, as well as with humans. Because wages are rising faster than labor productivity, especially in developing countries, manufacturing businesses are seeking more advanced robotics. For example, CNN Money reports that in China, the yuan is strengthening against the dollar, driving significant labor cost increases. More collaborative robots could enhance human productivity and in some cases replace the need to pay human laborers altogether.
However, development is hampered for now by the significant data processing resources that industrial IoT requires. Facilities lack the network speed needed to transmit massive amounts of data back and forth to remote data centers for analysis. Business Insider predicts that growth in mesh topology and edge computing should eventually eliminate these latency issues.
Mesh topology occurs when, instead of routing data through a central gateway, sensors bounce traffic between sensor nodes until it reaches the gateway. These networks are inherently self-organizing, which improves machine-to-machine communication. In addition, by performing basic data processing tasks locally rather than in a remote data center, edge computing should also enable faster cognitive computing operations, which would allow robots to react to their surroundings and respond to in-the-moment instructions.
IoT Data Analysis: Efficiency vs. Security
As manufacturers leverage big data more effectively, they can make real-time decisions for both stationary and collaborative robots. They can also cut costs by performing predictive maintenance and adjusting production volume based on market conditions.
At the same time, however, expanding sensor networks create new attack vectors and challenges for network security professionals. Whether it’s device-level authentication, application security or end-to-end service assurance, almost half of businesses surveyed by Morgan Stanley are concerned about security.
Collaborative robots require far more sensors than stationary machines, which could admittedly open up some network security vulnerabilities. At the same time, inevitable IoT, edge computing and cognitive computing growth should yield a perfect storm for the creation of interactive robots. The productivity gains from this innovation should counterbalance the risks.
As cognitive computing matures, robotics won’t be the only field that benefits — cognitive security options will expand at the same time. Just as automation and cognitive computing can power more advanced robots, they can also create more nimble defenses to offset cybersecurity concerns.