Xiamen, China, May 25 - Milesight is pleased to announce the launch of the AI ToF People Counting Sensor VS133. featuring dual technologies of on-board AI algorithm and 2nd generation ToF technology, it is ready to bring actionable insights to improve the values of applications based on people counting. The high accuracy of up to 99.8%, 100% anonymous detection, and more highlights enable value-added performance for especially smart buildings and retail businesses.
Dual Technologies Bring the Superior Performance
Featuring an onboard AI algorithm and 2nd generation ToF technology, it is a next-generation people counting sensor that allows for filtering unnecessary counts and distinguishing different crowds, which greatly improves accuracy and scenario adaptation for optimal performance. The upgraded technologies improve their capacity to boost applications.
Optimal Accuracy and Anonymous Detection
Based on the favorable ToF (Time of Flight) technology capturing in-depth images, the sensor is GDPR compliant truly realizing 100% anonymous detection. No personal identification information is involved at source. And the upgraded AI and ToF technologies allow to better filter non-object targets, lessen undetected probability, reduce dependence on installation height, and improve light anti-interference performance, contributing to an unparalleled 99.8% accuracy.
Advanced Performance Enhances Applicability
More than just the reliable counting of people in both directions simultaneously, the smart sensor also gives direct access to recognize specific categories of individuals including staff detection and adults/children differentiation, realizing precise people counting to optimize operational efficiency. By detecting the U-shape tracks, the sensor filters out redundant counting of people wandering the area to distinguish people who don’t truly enter. It can also perform well in all lighting conditions including low light or completely dark indoor environments and harsh outdoor environments with strong sunlight. What’s more the well-designed interfaces bring users a better interactive experience, more comfortable configuration processes, and more intuitive report data display.
Great Compatibility for Broader Applications
The alternative LoRaWAN® and Ethernet transmission help to flexibly make informed decisions for different application fields. The strong scalable capacity based on the open APIs and MQTT(s)/HTTP brings more possibility in compatibility and customized features to unlock the potential of the premises.
Typical Applications
The sensor can be applied anywhere, especially the smart buildings and retails, where people counting matters. It counts people, collects data, and delivers actionable insights to obtain informed insights into people counting and space utilization, enabling buildings to be smart enough for better performance in site performance, occupant experience, energy saving, cost saving, etc. For retail stores, supermarkets, or shopping malls that value people flow much for enhancing business running. Centering on real-time and accumulated statistics, the operators can easily discover peak hours for the greatest sales opportunities and get conversion rates through the customer volume to have a better understanding of the business's effectiveness. Furthermore, optimize staff management reasonably to fit customers’ actual needs.
The Sensor provides valuable insights to businesses and organizations about customer traffic and behavior with advanced performance. By accurately tracking the number of people who enter and exit a physical space or location, such as a store, mall, commercial building, or event venue, businesses can make data-driven decisions regarding their operations, marketing, and sales strategies. Overall, people counting is an essential tool for businesses and organizations looking to enhance their understanding of people’s behavior and improve their performance.
More Product Details at: https://www.milesight.com/iot/product/lorawan-sensor/vs133
Find More Highlights in the Video: https://youtu.be/dPrGVSz9RJ8
