RFID helps improve geographic location data accuracy

　　From mobile marketing to asset tracking, location has been a major driver influencing the widespread adoption of both consumers and businesses. GPS is an early example of how the combination of smartphones and positioning technology will change the way consumers and commercial vehicles drive on the road. Drivers have very low expectations and assume that on any long trip, even in the concrete jungle of parking lots, when signals from positioning satellites deteriorate and smartphones or other terminals lose orbit, the GPS will recalculate several times. The GPS is accurate and, in most cases, "accurate enough" for general civilian use.

　　Over the years, as location-based services, machine-to-machine communication, and the Internet of Things began to require positioning capabilities, new technologies started entering the market, primarily starting outdoors and then expanding to indoor asset tracking use cases across various industries. Wireless networks, RFID (RFID), Bluetooth beacons, and other technologies have emerged with the fundamental capabilities to meet this demand, essentially the ability to analyze received signal strength (RSSI). The question is, these Sontech technologies are not specifically built for positioning, let alone the real-time performance required by emerging applications, which limits their effectiveness and accuracy. However, in most cases, they are "precise enough" and have "tolerable latency" for the applications they use.

　　However, in recent years, the development of the Internet of Things and its emergence in non-industrial B2B markets have changed perceptions of positioning accuracy requirements. Driven by enterprise-wide efficiency, organizations are envisioning a range of applications that can use IoT, such as tracking smaller items or even people through embedded sensors on ID badges, aiming to interact with the environment. In fact, for every type of environment, several use cases are beginning to emerge, and even within the same field, there are different competitors. Meanwhile, significant technological advances have taken the form of real-time positioning systems (RTLS), providing sub-meter positioning capabilities. Even recently, the industry's positioning for emerging cutting-edge applications has surpassed the centimeter level—and in some cases, even smaller.

　　But do IoT and other applications require centimeter-level positioning? First, let's look at what positioning accuracy truly means for applications.

　　Understand accuracy

　　Accuracy in the sense of RTLS can be defined as a combination of precision and latency. High precision means that when tracking moving targets, the RTLS system can achieve accuracy from sub-meters (less than 1 meter) to centimeter-level accuracy, while still executing real-time follow-up with a delay time of less than one second. However, regardless of the technology used, achieving precision with low latency comes at a cost. Typically, high-precision real-time tracking is achieved by covering areas of interest with devices and creating data redundancy, which leads to increased initial system costs and, in some cases, overall cost of ownership.

　　Latency is another factor affecting RTLS accuracy. Not every application requires real-time location capabilities; for example, slow-moving heavy equipment may require position data spaced several minutes apart—a 10-ton object wouldn't move without a crane—and when tracking athletes, a delay of over 300 milliseconds is insufficient for augmented reality applications.

　　In most IoT applications today, centimeter-level accuracy and real-time tracking are not critical requirements. For example:

　　▲ Positioning forklifts in warehouses: accuracy within a few meters is acceptable, and positions within seconds rather than real-time are also acceptable.

　　▲ Positioning containers at shipyards: accuracy within a few meters is acceptable, and receiving position information within one minute is also acceptable.

　　▲ Moving large equipment around the oilfield: This application may require location data at intervals of several minutes, but location information within a few meters is usually acceptable.

　　However, some emerging applications require high-precision tracking, which may or may not include real-time capability requirements. Application examples requiring high precision include:

　　▲ Competitive Sports Analysis: Track the movement of athletes or objects, such as ice hockey skating in the arena. This requires real-time tracking down to a few centimeters, because athletes and equipment are always in motion, and their relative positions are crucial for describing game dynamics and specific events.

　　▲ Smart buildings: This may be related to optimizing hospital workflows while digitally processing the surrounding environment through a rule engine that simulates real-world logic; Interaction with home automation systems; Or export metrics that calculate contextual information. For example, turning on the lights when someone enters a meeting room, or analyzing shoppers' walking paths in supermarkets to obtain dwell time metrics and product interactions.

　　▲ Employee safety in industrial environments: In warehouse applications, workers and automated equipment move quickly from one place to another, requiring higher-precision real-time tracking to determine positions, such as avoiding collisions between forklifts and workers.

　　▲ Security and monitoring: This applies to any mission-critical scenario requiring highly reliable data and consistency, such as monitoring and access control.

　　Finally, the percentile of the standard deviation—also characterized by the cumulative distribution function—is another key factor for positioning accuracy.

　　If a location has high real-time performance, it means it must always meet standards of high-precision positioning and low latency—for example, 90% of the time, it is less than 1 meter.

　　Summary

　　The accuracy required to locate people or items depends on the specific requirements of the application itself and the business needs it supports. Looking at the example above, it's clear that in some cases, certain applications require more precise and lower-latency positioning capabilities than others. Organizations will determine their real-time location requirements based on the specific applications they are developing, and improved accuracy will continue to open the door to a large number of new applications.

　　It is important to note that when organizations determine their needs today, they also need to consider future applications, the precision required when they emerge, and at what scale. This is a key factor in reducing costs, improving profitability, and ensuring long-term investment. It is crucial to leverage an RTLS that can easily scale and integrate these new requirements according to business needs. This requires the implementation of highly flexible RTLS technology, in which the system can be configured for cross-border operation and offers accuracy from low to high. This makes it suitable for a wide range of applications, including secure and reliable workflow management, as well as advancing into augmented reality or virtual reality applications as demand arises.

　　Consistently determining the exact position of a person or object in real time is complex, and tracking static objects is often more difficult than tracking moving ones. No "silver bullet" can perfectly solve all use cases. Organizations must balance their specific needs with system costs (considering initial investment and total cost of ownership) to achieve their targeting capabilities, thereby achieving ROI that meets their business objectives.