Edge IoT technology brings industries real-time processing
IoT has extended the reach of technology beyond the traditional limits of a data center. Now that IoT devices have flooded network edges, new innovations bolster organizations to push past connectivity, security and compute limitations.
Developments for the edge and IoT, such as AI, have moved data analytics to quickly process data where it is created. With AI, organizations can derive actionable insights vital to exploring new use cases, increasing their automation and staying competitive in rapidly evolving industries. IT professionals can use these advancements for products or machines that need to make real-time decisions, or to enhance customer experiences with responsive features. The COVID-19 pandemic also introduced the need for real-time location and capacity data to alert people of possible exposure to the virus and to take proper precautions.
Edge and IoT technology can improve the safety of employees and consumers across industries, including healthcare, automotive and manufacturing. Quick AI insights at the edge could save lives through patient monitoring, split-second decisions in autonomous vehicles and machine failure predictions in a manufacturing facility.
To make these use cases possible, organizations must implement the right edge IoT architecture, which includes sensors, actuators, applications and gateways. The proper architecture is critical to handling the influx of IoT data, additional security risks introduced by edge devices and any future efforts to scale IoT projects.
In this handbook, discover what architectural elements organizations need at the edge and how the data lifecycle changes when used at the edge. Then, learn how AI algorithms can address the challenges that architecture and edge data processing present.