4.8 out of 5 stars
(6 Ratings)
Edgefinity IoT is a powerful RFID and IoT platform that gives organizations real-time visibility into inventory, assets, equipment, work-in-process, and personnel. By collecting data from RFID readers, sensors, and connected devices, the platform provides a clear view of what is happening across facilities and operations.
Edgefinity IoT helps businesses automate tracking, locate critical assets, monitor movement, verify inventory and shipments, improve production visibility, and support safety applications such as personnel tracking and emergency mustering. Configurable rules and alerts can automatically trigger actions when predefined conditions are met, helping teams respond faster and reduce manual oversight.
Built to work with a wide range of RFID hardware and IoT technologies, Edgefinity IoT can be deployed in the cloud or on-premise and scaled across applications, facilities, and enterprise operations.
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4.8 out of 5 stars
(132 Ratings)
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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Azure Face API
Incorporate facial recognition technology into your applications for an enhanced and secure user experience without the need for specialized machine learning knowledge. The system offers features such as face detection that identifies faces and their characteristics within images; individual identification that allows for matching against a private database of up to one million users; emotion recognition that assesses various facial expressions such as happiness, sadness, and fear; as well as the ability to recognize and cluster similar faces in photographs. You can identify faces based on a variety of attributes and integrate this functionality into your applications with just a single API call. The technology can operate seamlessly either in the cloud or on edge devices within containers. With a focus on enterprise-level security and privacy, it ensures the protection of both your data and the trained models. This platform enables the detection, identification, and analysis of faces in both images and video content, providing a robust foundation for a multitude of applications. Additionally, it supports the detection of multiple human faces along with their associated attributes in a single instance.
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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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