An Intelligent Video Analytics Platform

GIGABYTE has partnered with Gorilla Technology Group to deliver their Intelligent Video Analytics Recorder (IVAR) solution, using AI to implement facial, vehicle and behavior recognition technology of video streams from CCTV cameras.
In 1950, the fishing village of Shenzhen in south-east China had just 3,148 inhabitants. By 2025 it is predicted that number will exceed 12 million. In 1900 just 14 percent of people on earth lived in cities, but today over 55% of the world's population lives in urban areas, and the rate continues to grow. The UN predicts that by 2050 the percentage of people living in urban areas will edge closer to 70%.

Improving cities is a pressing global need as the world's population grows and our species becomes rapidly more urbanized. Thanks to the relative ease with which local governments can now gather real time data, combined with the capabilities of artificial intelligence, cities can now realize new ways to run more efficiently and effectively by combing their existing CCTV equipment and infrastructure with new and powerful computer vision technologies.

Not only governments can take advantage of this technology either - private organizations, including department stores or companies with large office buildings also often have a large deployment of CCTV cameras and related applications. These streams of video can also be combined with computer vision technology to implement "smart retail" and "smart security" solutions to generate business insights, decrease reaction times or reduce the need for staffing.
Real Case Scenarios
An intelligent video analytics platform can be used to recognize faces (including age, sex etc.), license plates and objects (and compare them with a database for matching) and track the speed and movement of people and vehicles to establish patterns. It can be used to help implement "smart retail", "smart security" and "smart city" solutions.

Smart Airport Retail
Gorilla's IVAR was deployed as a smart retail solution into Taipei International Airport. Management can now access real-time information such as people count, traffic flow and track passenger flow-to-purchase using beacon technology. Understanding the number of in-store customers and traffic flow trends enables managers to make better decisions for staffing to ensure operational efficiencies.
Safer Public Transportation
Gorilla's IVAR was deployed at a busy transit station in central Taiwan with more than 17,000 daily travellers and limited security staff. The system can now recognize people on watch lists, monitor footfall traffic, analyze abnormal behavior, detect unlawful intrusions and more. With IoT sensors built into the IVAR system, authorities can detect fires and intrusions on the tracks or other areas.
Using Intelligent Video Analytics to Create a Smart City
Almost all major cities now have a network of CCTV cameras installed, both in and around public installations (such as airports, train stations) as well as on the roadside to monitor traffic. NVIDIA predicts that by 2020 there will be 1 billion cameras deployed on government property, infrastructure, and on commercial buildings.

Not only is the number of CCTV cameras increasing, but also the quality and resolution of the images and video recorded by these cameras. IHS MARKIT predicts that by 2022, up to 60% of CCTV cameras shipped worldwide will have a resolution of 4 megapixels or higher, resulting in a marked increase in the quality of usable video. This huge source of raw video has a massive potential to be used more effectively to provide intelligence to local governments and business in order to improve public & customer safety, security and convenience.
Using Intelligent Video Analytics to Create a Smart City
However, the huge increase in raw video means that it will become impossible for most footage to be viewed live or after the fact by human operators. For example, manually reviewing 1 hour of video can take up to 2 – 2.5 hours. Most video is then either deleted permanently or archived without being used for any meaningful analysis.

Advances in artificial intelligence mean that applications can now take on image recognition capabilities that allow them to detect and identify human faces, vehicle registration plates, and other objects. An intelligent video analysis platform can be used to recognize faces, license plates and objects (and compare them with a database for matching) and track the speed and movements of people and vehicles to establish patterns.
Facial Recognition with Artificial Intelligence
Furthermore, by using machine learning, video analysis and image recognition can become faster and more accurate over time. The more often a computer performs this sort of analysis, the more capable it becomes of correctly identifying and tagging other images in the future. Larger datasets lead to more accurate results, and feedback loops help eliminate errors.
suitable to Performance, Efficiency
All-in-One VMS & IVAR Solution
Comprehensive yet compact Video Management System with Intelligent Video Analytics, ideal to take all-in-one and proactive video surveillance.
suitable to Flexibility, Scalability, production capacity
Flexible & Scalable with Client Needs
Scalable and flexible use from all-in-one machines or gateway hubs to large server scenarios.
suitable to Reduce Expenses, Money Saving, Reduces Cost
Adding Value with API Integration
Open architecture and API interface for quick integration with existing VMS solutions (e.g. Milestone) and other platforms.
Intelligent Video Analytics Platform Architecture
Gorilla's IVAR (Intelligent Video Analytics Recorder)
Gorilla's Intelligent Video Analytics Recorder (IVAR) solution extracts surveillance video insights and delivers actionable facial, vehicle and object identification results for government and commercial entities. Compatible with industry protocols and standards like ONVIF, RTSP and H.264, this solution can be deployed on edge devices connected to video cameras, or integrated directly into devices with built-in cameras. Gorilla's IVAR offers value-added applications in different verticals like public safety, industry, retail, banking and education and provides advanced dataset services for cloud servers.
Gorilla IVAR Overview
Gorilla's Backend Application Suite
Gorilla provides a suite of powerful backend applications which can be run on a public, private or hybrid cloud. Video streams are collected on Gorilla IVAR edge devices or edge servers for preprocessing and then forwarded for analysis. Here, unstructured video and image data is transformed into structured data via deep learning. Events are stored in software defined storage and correlated and categorized for use in biometric authentication, account management, device management, and business intelligence.

BAP (Biometric Authentication Provider)
・The BAP (Biometric Authentication Provider) is a database of personal profiles with images, that verifies personal identities via facial images captured from the IVAR edge device / server
・Client / server mode: facial recognition is conducted on the BAP server. Then, the result is pushed to the edge device for the further action, e.g. granting entrance access.
・Client mode: the BAP database is synchronized with edge devices / servers to enable facial recognition functions on the edge.

EVMS (Event and Video Management System)
・Manage IVAR devices, video channels, and IVA events
・Store event logs for archived search

FVS Fast Video Search
・Identify human faces or vehicle registration plates from IVAR's live streaming or uploaded H.264/MPEG 4 files, and stores them into an EVMS database.
・View captured face / vehicle images from selected time periods and locations.
・Search people or vehicles different attributes. E.g. eyewear, clothes color, car type etc.

Dataset & Training Service
・Store and archive sample images collected from Gorilla's IVAR with object attribute information e.g. gender, age, license plate.
・Use these images as a subset to generate new machine learning algorithms.
・For example, use a filter tool to select relevant samples (US license plates) and manually label California license plate images.
・Then, use those labeled images to train new deep learning models to recognize California license plates.

Gorilla's Dataset and Training Service User Interface
GIGABYTE Server Hardware
Gorilla has qualified and recommends the following GIGABYTE servers for an Intelligent Video Analytics Platform turnkey solution
IVAR Server
G191-H44 (rev. 100/200)
G191-H44 is an ideal compact form factor GPU server, providing a capacity of 4 x GPU cards ideal for inferencing purposes of multiple video streams.
EVMS / FVS / BAP Server
R181-340 (rev. 100)
R181-340 is an ideal cost and performance efficient solution for hosting the back-end applications of an Intelligent Video Analytics Solution.
Dataset & Training Service Server
G291-280 (rev. 100)
G291-280 is an efficient and powerful platform for machine learning applications, providing an industry leading density of 8 x GPU cards in a 2U form factor server.
Related Technologies
Cloud Computing
In simple terms, Cloud Computing is the delivery of computing services to a user or an organization—servers, storage, databases, networking, software, analytics, intelligence and more—over the Internet ("the Cloud"). Cloud Computing is usually provided using virtualization, in where the physical computer hardware is abstracted from the software & applications that are running on that hardware. Cloud Computing services can be provided several different ways, via public, private or hybrid clouds. Public cloud computing is provided by 3rd party service providers (such as Amazon Web Services, Microsoft Azure, or Google Cloud) who own the physical hardware and then sell these resources online via a secure internet connection. In a private cloud, an enterprise builds a cloud within their own data center by running applications on virtual servers that may reside on any number of available physical machines. Hybrid cloud computing is where a mixture of private and public cloud computing services are used together in tandem. As part of RightScale's 2018 State of the Cloud report, an in-depth survey was conducted of 997 IT professionals about their adoption of cloud infrastructure and related technologies, an astonishing 96% of respondents indicated that they run their enterprise's workloads in a cloud – either public, private or hybrid.
Parallel File System
A parallel file system, also known as a clustered file system, is a type of storage system designed to store data across multiple networked servers and to facilitate high-performance access through simultaneous, coordinated input/output operations (IOPS) between clients and storage nodes. A parallel file system breaks up a data set and distributes, or stripes, the blocks to multiple storage drives, which can be located in local and/or remote servers. Users do not need to know the physical location of the data blocks to retrieve a file, as the system uses a global namespace to facilitate data access. Data is read / written to the storage drives / devices using multiple I/O paths concurrently, providing a significant performance benefit. Storage capacity and bandwidth can be scaled to accommodate enormous quantities of data, and features may include high availability, mirroring, replication and snapshots.
Multi-access Edge Computing
What is Multi-access Edge Computing (Mobile Edge Computing)? Multi-access Edge Computing (MEC), also known as Mobile Edge Computing, is a network architecture that enables cloud computing capabilities and an IT service environment at the edge of a cellular network. MEC technology is designed to be implemented at cellular base stations or other edge nodes, and enables flexible and rapid deployment of new applications and services for customers. MEC is ideal to be used for the next generation of 5G cellular networks.
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