NICE Alliance Announces Key Specifications to Bring the Next Generation of Smart Cameras to Market

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Industry Leading Network of Intelligent Camera Ecosystem (NICE) Alliance unveils its V0.9 specification and features for public review in advance of the final version


PALO ALTO, CA, March 26, 2019 – Last year, leading consumer electronics manufacturers and brands Foxconn, Nikon, Scenera, Sony Semiconductor Solutions and Wistron collaborated to formally create an innovative ecosystem standard for smart camera markets with the aim to provide an open data sharing platform based on video/image and AI to enhance the synergistic effect of multi-brand, multi-camera, and multi-service/app. Since the consortium’s inception, Allion, Augentix, Mobilicom and TnM Tech have joined NICE alliance as contributors. After a year of collaboration and joint development, NICE Alliance today releases the first public review of specifications and detailed features on its blueprint and technology, with a goal to publish a finalized version for formal adoption by the second half of 2019.

Founded on a vision to propel and advance real-time video image analytics to bring forth the next era of smart cameras to the consumer and enterprise markets, NICE Alliance aligns with leading manufacturers and suppliers including sensor makers, camera modules and cloud system solutions to drive adoption across the industry.

Currently, the management of Artificial intelligence (AI) processing has been limited within cloud-based data centers, which require a heavy computing capacity and intensive training of deep learning models. Providing a solution to the issues surrounding security, data privacy, bandwidth, latency requirements and cost constraints, NICE has identified the need to develop decentralized architectures, enabling AI processing to be performed on such edge devices including cameras and on advanced image sensors. This new process ultimately creates a distribution of AI capabilities for efficient and formal sharing on the cloud, the camera or IoT devices and image sensors.

With the massive increase of high-resolution camera products in the market, the amount of generated raw video data has become too large for practical streaming. With the difficulty to predict the nature of video images and manage the huge volumes of video data (which only carry a small amount of relevant video information), existing standard compression technology has yet to address this problem. NICE’s edge AI capabilities provides a tangible solution and increases efficiency by sorting images on the edge, ensuring that only relevant video information is sent to the cloud.

While the need for balancing between the edge and the cloud is clear, building this needed distributed AI network requires the industry to address the challenge of sharing AI tasks between the edge and the cloud. One of the main reasons for the NICE Alliance formation is to create a standard defining a pipeline and data architecture that provides an ideal solution for efficient decentralization of AI computing.

Designed to drive adoption of its ecosystem, NICE Alliance is publishing a specification that can capture scene-based images or video streams containing an abundance of specific information, such as image frames, audio, and metadata, in cameras. The NICE Specification defines a new standard way for camera devices, cloud services and apps to communicate with each other and establish an effective solution, enabling a new class of utility services for consumers and creating new opportunities and business models for emerging applications.

Key features of NICE include:

  • Secured Camera and Application Management – NICE Cameras connect directly to the cloud server for secure automatic configuration. A simple app enables users to link the camera to their accounts using centralized security server that manages encryption keys and password credentials on behalf of the user.
  • Scene-based Application Interface – Application developers can easily determine the capabilities of cameras including their analytical capabilities for vision processing. Scene-base image capture means that an app developer can set a SceneMode to configure a data stream describing events that occur in the camera’s field of view, including relevant video clips, metadata generated locally by processed analytics and auxiliary data such as audio and other environmental senses. Multicamera curation further sorts the data from multiple cameras. This removes the need for applications to handle raw video directly and reduces the cost of processing and storing multiple video streams.
  • Layered Camera Interface – NICE enables to reduce the complexity of integration for camera makers. The layered interface enables the camera to expose advanced image capture and image processing capabilities to applications. Video analytic algorithms can be performed at different layers enabling optimized image capture using sensor’s or camera’s capabilities. This results in image capture and locally processed video stream data that is optimized for the cloud-based video analytics AI algorithms to work much more efficiently.
  • Distributed AI Management – NICE allows applications to distribute Artificial Intelligence algorithms to where they can perform best for real-time analytics. Analytical algorithms can be executed in sensors or camera or in the cloud to enable managing multiple streams of video images for a fast and accurate analysis. This resembles the human vision system where simple reflex actions are processed in the spinal cord for fast response, while the brain handles complex processing.

Seamlessly integrating the standardization of advanced IP cameras in surveillance and IoT markets with cloud-based machine-learning and AI applications require participation from broad ecosystem players including sensor makers to big data AI solution providers. “NICE will incorporate challenging concepts of distributed computing and layered virtualization into streaming video data pipeline to meet broad acceptance by end-users in multiple industries”, said David Lee CEO of Scenera. “NICE promoters are focused on importing powerful concepts used in other computing devices, such as smartphones, into imaging devices, with its unique data processing and advanced end-user demand for emerging and future products. NICE will redefine how imaging devices can enrich end-user experience, while creating new business opportunities for all ecosystem players from sensor makers to cloud solution providers.”

NICE manufacturing adopters expect availability and longevity of third-party applications and services for different classes of cameras, focusing on innovating camera features and improving performance. “We look forward to the final release of the NICE specification. We are excited for NICE’s innovative capabilities to bring a new trend to the intelligent data-rich camera industry and extend the business scope to highly in demand cloud applications,” said Shengwei Yang, Vice President of Production and Solution at Dahua, a leading global smart camera maker.

NICE manufacturing adopters expect interoperability of NICE compliant products, offering an authorized test center (ATC), crucial for ease of use for consumers, third-party applications and service developers. “We are excited for NICE’s innovative capabilities to bring a new trend to the intelligent data-rich camera industry and extend the business scope to highly in-demand cloud applications,” said Mr. Nakayama, President of Allion Japan, a leading testing and consulting service company, whole AIoT ecosystem provider and one of NICE Alliance’s key contributors. “We look forward to the final release of the NICE specification and providing HW/SW and Interoperability testing for manufacturing adopters and application developers.”

AI-based video analytics is rapidly advancing and improving in the cloud. Many industry experts agree that one of the major features of the NICE specs, not covered in any other industry standardization efforts, is the ability to distribute AI computing across sensors, cameras and in the cloud by defining a new layered control, ultimately utilizing virtualization between layers. This key attribute allows cloud apps and services to more effectively capture appropriate images from sensors and further analyze data in the camera at a very low latency, satisfying end-user demands cost effectively.

NICE Alliance continues to develop its infrastructure and establish guidelines for the ecosystem, which will be open for all companies and interest groups who would like to participate in contributing and adopting the specifications. NICE’s current V0.9 specification can be found here:, and V1.0 specification is expected to be released in mid Q2-2019.



Scenera is forging a new standard for the surveillance and IP camera market with imaging solution providers. The visionary founders see the paradigm shift from color-rich images to rich scene information that enables new and powerful capabilities. Standard compliant smart cameras generate abundant image information for surveillance applications such as object recognition and detection, location tracking, etc. Scenera’s goal is to align key industry players with the same vision to create an interoperable ecosystem that will bring a new generation of the smart camera. Scenera is a licensed and administrative agent of the NICE alliance.

For more information, please visit




Lydia You | Scenera, Inc.



Kiyohisa Ota (太田清久) | Scenera, Inc.

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