Using Camera Data Effectively Without Facial Recognition

For example, Sixgill, LLC, a leader in data automation and authenticity for Internet of Everything (IoE) applications, announced just such a solution that preserves and improves the value of cameras in the enterprise without the liabilities of privacy-violating facial recognition.

Sense Vision – a newly launched capability in Sixgill’s foundational product, Sense – delivers real-time video data automation, assisted by machine learning (ML).

Sense Vision features the breakthrough Sense Vision Positioning System (VPS) for object location and movement tracking without the need for mapping data or instrumenting objects or people being tracked.

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display(div-gpt-ad-1439400881943-0); }); The result is always-on, unblinking video camera intelligence that enables live, remote monitoring for use cases such as workforce management, safety, security, regulatory compliance and other needs for monitoring and engaging people, spaces and things – without facial recognition.

Sixgill goes even further to provide more options for greater privacy: The camera data does not have to be stored on servers or in the cloud.

Sense Vision Edge capabilities enable deployment on or near the camera itself allowing responses to what it sees in the moment without the need for data retention.

Thus, Sense Vision imagery can be acted upon but not retained, when privacy safeguards are paramount.

Video cameras are commonplace because of their ability to perform continuous real-world information gathering.

With advancements in connectivity, Edge Computing and Machine Learning, smart cameras can deliver more value to real-time operations.

According to Gartner, by 2020, 65% of enterprise-captured video/image content will be analyzed at least partially by machines.

Increasingly, organizations are facing difficult challenges to accurately and comprehensively capture this high-intensity data and use it effectively without relying on human monitoring.

Sense Vision combines new and existing capabilities in Sixgill Sense allowing for unified, high performance data collection and automation.

Camera data is ingested via the Sense Vision Data Pipeline and prepared for deep learning and analysis.

Sense Vision processes and enriches live video data with existing or custom ML classifications, object recognition or entity extraction models Previously announced, Sense ML provides for easy and rapid deployment and lifecycle management of training data and ML models.

Based upon business needs, configurable rules can be assigned so that actions such as real-time alerts and system responses are triggered when ML assisted analysis detects anomalies or recognizes actionable behaviors Part of Sense Vision, VPS is an industry breakthrough that enables automated positioning and proximity determination of objects using monocular camera image analysis only—no external mapping data or extraneous instrumentation are required.

As people and objects within camera imagery are annotated for ML model training data sets, VPS automatically calculates each labeled object’s location, and with Vision Depth Perception (VDP), measures the proximity distance of one object in relation to another, as well as the distance the object moves within the camera view over time CIOs and CTOs can now capture the full value of their enterprise-wide camera data collection and analysis with fully automated, data-driven actions at scale.

Custom dashboards make continuous metrics monitoring and system administration easy.

Always-on, unblinking video camera intelligence enables remote live monitoring and management of business operations across use cases for workforce management, worksite operations, people/spaces/things monitoring and engagement, safety, security and regulatory compliance.

Sense Vision provides: Monitoring and tracking location, volume, movement, and behavior of people and things Understanding building, room, and common space utilization Detecting objects, identifying activities and behaviors, and triggering real-time actions Enforcing location- and situation-based safety, security, and compliance Greater privacy safeguards in networked camera deployments “We encounter many customers for whom the camera is the sensor of first resort.

Cameras are understood and easy to implement, posing less mystery to buyers than mixed-sensors networks.

We built Sense Vision with Machine Learning capabilities to maximize customers’ value of camera data in real-time operations,” said Elizabeth Shonnard, Senior Vice President, Products, at Sixgill.

“Sense Vision is a natural extension to Sense, as video is just another form of time-series data, for which Sense is comprehensively optimized, at whatever frames-per second rate video is captured.

” Sense Vision delivers insights and programmatic responses from video data streams flexibly in the Cloud, at the Edge, or both.

To take advantage of Edge computing efficiency and ensure personal privacy protection, Edge deployment on the cameras themselves provides reduced processing costs, low-latency immediacy, and greater personal privacy With all camera deployments, ensuring privacy is crucial, particularly in use cases such as worksite monitoring for policy compliance, space occupancy and utilization, as well as guest experience.

Unlike other solutions, Sense Vision does not depend on facial recognition, and data does not have to be stored on servers or in the cloud.

By responding on the camera to what it sees in the moment, Sense Vision imagery can be acted upon but not saved, therefore safeguarding personal privacy.

Sixgill’s Sense Vision serves enterprises that demand complete ownership of data, freedom from data balkanization, and autonomy from lock-in proprietary contracts.

Product owners and developers benefit from Sixgill professional services to assist with custom use case applications requiring speedy deployment and flexibility for custom or existing ML models offering continuous intelligence and decision automation that improves with time as more data is added.

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