In its most fundamental sense, telematics combines telecommunications technology with informatics—the science of computing systems and data. With the development of the Internet of Things (IoT), this field has become a focal point. A wide range of business activities, from fleet management to manufacturing, now rely on telematics. Industry 4.0 combines telematics and automation. Below is a close examination of the intersection of these two innovations.
Machine Learning Navigation
Perhaps the most famous example of the collaboration between telecommunications and robotics is advanced navigation systems. Machine learning algorithms may not be what people think of when they hear "robotics," but they are a type of software robot. Today, some logistics companies use machine learning to process telematics data and navigate more efficiently.
The most prominent example of AI-based navigation is UPS's Road Integration Optimization and Navigation (ORION). ORION analyzes road conditions, weather, and traffic to determine the most efficient route for drivers. UPS states that the system reduces each driver's journey by 8 miles, resulting in significant savings in time and fuel.
To achieve these savings, systems like ORION require telematics and robotics. Telematics collects and transmits data, which is then processed by software robots to generate actionable insights.
Real-time remote monitoring
Just as telematics encompasses more than just transportation, so too does the intersection of telematics and robotics. With the rise of Industry 4.0, more and more manufacturers are integrating IoT connectivity into their facility's robotic systems. This trend utilizes telematics technology to make real-time data from factory robots remotely accessible.
A major benefit of robotics is increased efficiency, but halting production to inspect robots can hinder productivity. The answer lies in using telematics to send operational data to the cloud or remote devices. Manufacturers can then view the condition and operational efficiency of robots without physically inspecting them. Remote access to real-time operational data allows manufacturers to see if and how their robots can be improved. They can then make more informed decisions regarding workflow restructuring or investing in future automation systems.
Predictive maintenance
One of the most valuable applications of this remote data monitoring is predictive maintenance. Traditional maintenance relies on accurate record-keeping, which workers often neglect due to the pressures of daily work. Predictive maintenance offers a solution by using sensors to determine when attention is needed and remotely alerting workers.
Poor maintenance strategies can reduce factory productivity by 5%-20%, primarily due to downtime. Predictive maintenance prevents this by anticipating problems before they lead to failure, allowing workers to address issues with minimal disruption. Similarly, this strategy ensures that each machine or vehicle receives only the necessary maintenance, preventing unnecessary repairs that can also cause downtime.
Because robots represent a significant investment, many factories use predictive maintenance to keep their systems in optimal condition. Like the robotics technology itself, these maintenance strategies have high upfront costs, but yield substantial savings over time.
Remote operation
A newer but growing area at the intersection of telematics and robotics is remotely operated robots. While remote work has increased in recent years, some jobs, such as those in factories or hospitals, are not suited to remote work. Remote operation enables workers such as doctors and machine operators to perform delicate tasks remotely.
Remotely controlled robots enable world-leading experts to share their skills with people around the world. For example, in 2019, Chinese doctors performed surgery 1,900 miles away from a patient. Thanks to improvements such as 5G connectivity, telematics networks can now support such sophisticated remote operations with latency of only milliseconds.
Similarly, factory workers can control robots from home using telematics. This gives these employees flexibility in areas they didn't have in the past. If a factory needs to reduce its on-site reception capacity for health reasons, they can now do so without sacrificing productivity.
Mobile robots
Remote communication can also help robots control themselves. While most industrial robots are currently stationary, mobile robots have become increasingly common with technological advancements. These machines typically rely on a combination of sensors and remote communication services to navigate safely and efficiently in the workplace.
Material handling and picking are often repetitive and inefficient processes, making them ideal for automation. Remote communication networks within a factory or warehouse can guide robots to the correct items and then show them where to take them. This combination of automation and precise positioning technology can make these historically slow processes much more efficient.
With advancements in telematics technology, mobile robots can work in new use cases and travel greater distances. This movement is already underway, with food delivery robots expected to enter many campuses this year.
self-driving cars
The logical next step for mobile robots, and perhaps the most anticipated application of telematics and robotics, is the self-driving car. These machines rely on sophisticated telematics technologies and robotic processes such as machine learning for navigation. While self-driving cars may still be years away from widespread use on the streets, this future is steadily drawing closer.
Long-haul trucking is an ideal early use case for autonomous driving technology because it utilizes long, straight routes and highways offer more predictable traffic volumes. The fact that TuSimple, an autonomous trucking startup, plans to launch driverless routes this year suggests that self-driving trucks may not be far from becoming a reality.
Telematics and robotics must both advance for self-driving cars to become widespread. As each technology gains wider adoption, they will acquire the data needed to drive progress.
Telematics and robotics are becoming increasingly intertwined.
As technology advances, these fields are becoming increasingly intertwined. Telematics and robotics may have once been entirely separate sciences, but today they work together in many applications. From here, they will likely only become more closely integrated until they are inseparable in many industries.
These examples are just a few use cases for telematics and robotics. While this may not be immediately apparent, the intersection of these technologies is already ubiquitous and growing daily, and together they could completely revolutionize the industrial world.
