SMS Storetraffic
Smart, efficient, anonymous People Counters & Analytics to the real world.
Our solution allows for easy deployment, capture, analysis, and reporting of the number people who enter a physical place. Optionally, we can also capture and report occupancy in real time.
We assist Retailers, Universities, Casinos, Places of Worship, Office Buildings, and other industries in analyzing and taking action on their people traffic trends.
We offer a special package for retailers to measure performance on traffic, including conversion rate and service levels. Our direct integrations make it easy to combine POS data with staff data. The Retail Equation simulator lets users run simulations to improve sales. It can also be used as a learning tool to understand how traffic, staffing, conversion rates, and quality service relate.
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QBench
QBench allows you to keep track of all your samples and where they are located in the workflow using a single system. QBench eliminates the need for spreadsheets, shared folders in the network, and paper-based tracking systems. You can view hundreds of PDF reports/COAs before publishing or emailing. You can generate barcodes and create labels that you can customize for your samples. Compatible with standard printers and scanners. QBench's billing module allows you to create and send invoices right from the system. You can see counts and latencies for different data types in QBench. This includes metrics like turnaround time, sample counts per test, sample delay, and many others. QBench makes it easy for you to gather the data your lab needs for the assays you perform.
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Retail Sensing
Testing indicates that video-based people counting systems can achieve accuracy rates exceeding 98%. This remarkable accuracy is achieved without compromising anonymity. An overhead CCTV or IP camera monitors the movement of individuals within a designated area. This camera is connected to a people counter that precisely detects and logs the number of individuals passing through a specified counting zone. The data collected by these counters can be transmitted via various methods, including Wi-Fi, the Internet, IoT protocols, IP, Ethernet, RS485, or RS232. By integrating these counts with real-time sales data from a POS system, businesses can obtain immediate insights into their sales conversion rates. To effectively manage wide entrances and expansive areas, multiple cameras can be interconnected across the ceiling. Additionally, an embedded video server provides the capability to view live footage alongside the corresponding people counts, allowing for accurate verification and configuration of the system remotely. After initial setup, the system can be optimized to transmit only the count data over the network, which helps conserve bandwidth. For off-site commissioning, it is also possible to replay the videos used for counting. This multifaceted approach not only enhances data accuracy but also improves operational efficiency.
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Amazon Rekognition
Amazon Rekognition simplifies the integration of image and video analysis into applications by utilizing reliable, highly scalable deep learning technology that doesn’t necessitate any machine learning knowledge from users. This powerful tool allows for the identification of various elements such as objects, individuals, text, scenes, and activities within images and videos, alongside the capability to flag inappropriate content. Moreover, Amazon Rekognition excels in delivering precise facial analysis and search functions, which can be employed for diverse applications including user authentication, crowd monitoring, and enhancing public safety.
Additionally, with the feature known as Amazon Rekognition Custom Labels, businesses can pinpoint specific objects and scenes in images tailored to their operational requirements. For instance, one could create a model designed to recognize particular machine components on a production line or to monitor the health of plants. The beauty of Amazon Rekognition Custom Labels lies in its ability to handle the complexities of model development, ensuring that users need not possess any background in machine learning to effectively utilize this technology. This makes it an accessible tool for a wide range of industries looking to harness the power of image analysis without the steep learning curve typically associated with machine learning.
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