Video Surveillance software - Expert commentary

Edge Computing, AI and Thermal Imaging – The Future of Smart Security
Edge Computing, AI and Thermal Imaging – The Future of Smart Security

Smart security is advancing rapidly. As AI and 4K rise in adoption on smart video cameras, these higher video resolutions are driving the demand for more data to be stored on-camera. AI and smart video promise to extract greater insights from security video. Complex, extensive camera networks will already require a large amount of data storage, particularly if this is 24/7 monitoring from smart video-enabled devices. With 4K-compliant cameras projected to make up over 24% of all network cameras shipped by 2023 – there is a fast-growing desire for reliable storage on-board security cameras. The question for businesses is: do they look to break up their existing smart video network, by separating and compartmentalising cameras to handle data requirements, or do they increase its storage capabilities? As some people begin to venture out and return to work following initial COVID-19 measures, we are also seeing demand for thermal imaging technology increase. New technology like this combined with more of these always-on systems being rolled out, means organizations will need to carefully consider their smart video strategy. Newer edge computing will play an important role in capturing, collecting, and analyzing data and there are some key trends you can expect to see as a result of this evolution. There are many more types of cameras being used today, such as body cameras, dashboard cameras, and new Internet of Things (IoT) devices and sensors. Video data is so rich nowadays, you can analyze it and deduce a lot of valuable information in real-time, instead of post-event. Edge computing and smart security As public cloud adoption grew, companies and organizations saw the platform as a centralized location for big data. However, recently there’s been opposition to that trend. Instead we are now seeing data processed at the edge, rather than in the cloud. There is one main reason for this change in preference: latency. Newer edge computing will play an important role in capturing, collecting, and analyzing data Latency is an important consideration when trying to carry out real-time pattern recognition. It’s very difficult for cameras to process data – 4K surveillance video recorded 24/7 – if it has to go back to a centralized data center hundreds of miles away. This data analysis needs to happen quickly in order to be timely and applicable to dynamic situations, such as public safety. By storing relevant data at the edge, AI inferencing can happen much faster. Doing so can lead to safer communities, more effective operations, and smarter infrastructure. UHD and storage AI-enabled applications and capabilities, such as pattern recognition, depend on high-definition resolutions such as 4K – also known as Ultra High Definition (UHD). This detailed data has a major impact on storage – both the capacity and speeds at which it needs to be written, and the network. Compared to HD, 4K video has much higher storage requirements and we even have 8K on the horizon. As we know, 4K video has four times the number of pixels as HD video. In addition, 4K compliant video supports 8, 10, and 12 bits per channel that translate to 24-, 30- or 36-bit color depth per pixel. A similar pattern holds for HD — more color using 24 bits or less color using 10 or 12 bits in color depth per pixel. Altogether, there is up to a 5.7x increase in bits generated by 4K vs. 1080 pixel video. Larger video files place new demands on data infrastructure for both video production and surveillance. Which means investing in data infrastructure becomes a key consideration when looking into smart security. Always-on connectivity Whether designing solutions that have limited connectivity or ultra-fast 5G capabilities, most smart security solutions need to operate 24/7, regardless of their environment. Yet, on occasion, the underlying hardware and software systems fail. In the event of this, it is important to establish a failover process to ensure continued operation or restore data after a failure, including everything from traffic control to sensors to camera feeds and more. Consider the example of a hospital with dozens or even over a hundred cameras connected to a centralized recorder via IP. If the Ethernet goes down, no video can be captured. Such an event could pose a serious threat to the safety and security of hospital patients and staff. For this reason, microSD cards are used in cameras to enable continuous recording. Software tools – powered by AI – can then “patch” missing data streams with the content captured on the card to ensure the video stream can be viewed chronologically with no content gaps. Thermal imaging Health and safety is the number one priority for all organizations as people return to work and public spaces. Some organizations are deploying thermal imaging to help screen individuals for symptoms as they return. Organizations that operate with warehouses, depots and assembly lines will traditionally have large amounts of cameras located outside of the entrance. With thermal imaging smart video in place, these cameras can now serve a dual purpose as a screening device. The thermal imaging technology is capable of detecting elevated body temperatures, with 10-25 workers being scanned in one shot, from one camera – making it an efficient and accurate process. This way, staff can use the information to help identify people who may need further screening, testing, and/or isolation before returning to work. There are many more types of cameras being used today, such as body cameras, dashboard cameras, and new Internet of Things (IoT) devices While this may not increase data storage requirements, it can change your retention policies and practices. Smart security today is about utilising AI and edge computing, to deliver an always-on, high-resolution video provision that can help keep people safe 24/7. These trends increase the demands and importance of monitoring, which means requirements of the supporting data infrastructure improve to match that, including the ability to proactively manage the infrastructure to help ensure reliable operation. Companies need to make sure they have considered all the storage and policy challenges as part of their smart security strategy for the future.  

The New Marriage Between AI and Stadiums
The New Marriage Between AI and Stadiums

Stadiums around the world are still paralyzed from the effects of COVID-19. Fans and spectators in masses have been absent from stadiums since April and there doesn’t seem to be a concrete plan on how or when they’ll be able to return to near capacity. The NBA recently opted to form a bubble philosophy concept in Disney’s facilities, although it’s been a relative success, it’s also been a $200 million temporary solution. This then begs the question: How long can stadiums survive like this without spectator’s present? History tells us that stadiums, venues and sport recover from disasters, so what can stadiums do to speed up the process? This is the catalyst for AI to be integrated on mass level to stadiums around the world. AI is the answer AI’s role in getting fans and spectators back is huge, through capabilities such as: Social Distance Monitoring Crowd Scanning/Metrics Facial Recognition Fever Detection Track & Trace Providing Behavioural Analytics Technologies such as IREX.ai is now working alongside National Leagues, Franchises and Governing Bodies to implement AI surveillance software into their CCTV/surveillance cameras. This is now creating a more collaborative effort from the operations team in stadiums, rather than purely security. Stadiums around the world are still paralyzed from the effects of COVID-19 AI surveillance software such as IREX.ai when implemented into the surveillance cameras can be accessed by designated users on any device and on any browser platform. Crowd metrics Arming stadiums with AI-powered surveillance tools can detect crowd metrics such as “people counting” and “group statistics”. This ensures stadium personnel can monitor social distancing with precision, accuracy and immediately. Alerts can be set up throughout parts of the stadium to alert senior staff members when overcrowding can appear with real time videos, analytics and photos to their hand-held device, such as a smartphone. Fever detection Thermal cameras have been implemented throughout facilities including stadiums and are helping assist to spot people with elevated temperatures. What IREX.ai implements is an alert system, coupled with facial recognition of any individual(s) that read an elevated body temperature. This alert system then provides security and health officials with a photo of the individual with the elevated body temperature, meaning staff can react quicker to the situation prevent this individual from entry. Pandemic monitoring by facial recognition  Thermal cameras have been implemented throughout facilities including stadiums and are helping assist to spot people with elevated temperatures Through facial recognition, staff members will be able to locate individuals through simply uploading a photo. It has never been easier to find a person of interest. With masks becoming an everyday part of society, facial recognition has come under scrutiny regarding the accuracy when a mask is worn. Irex.ai still maintains a 96% accuracy with individuals wearing masks and can set up alerts for any individuals not wearing a mask. Another important aspect of facial recognition is finding persons of interest quickly through technology like IREX.ai’s “searchveillance”. The future is here. Designated staff can track a person from when they enter the stadium by simply uploading their photograph. An example of how this can assist stadium personnel is to help relocate lost children inside the stadium with their guardians/parents when they are separated. Another attribute would be any individuals banned from entering the stadium would trigger alerts once they appear under surveillance, a fantastic collaborative tool to use with Law Enforcement.    Return on investment With security solutions, one of the biggest issues with any security investment is a lack of an ROI. This is where AI security is breaking the mould. The ability to provide business analytics, consumer/fan behaviours, traffic patterns, etc, allows other departments within the organization to gain vital information that can assist with their strategies and practices. Stadium security will never be the same in a post-COVID world, so why will its practices stay the same? AI & Stadiums is no longer the future, it’s the 2020 solution.

Reopening Doors: What Steps Should be Taken to Ensure Safety and Security?
Reopening Doors: What Steps Should be Taken to Ensure Safety and Security?

A total of £1.6 billion worth of goods are reported as ‘lost’ to in-store theft in supermarkets each year, with figures increasing steadily. The presence of self-checkout systems have increased in supermarkets, as well as other industry retailers. By 2021, we’re globally on track to have 468,000 self-checkout machines in operation, nearly double the 240,000 in existence since 2016. While this increase comes with such benefits as reduced wait times for customers and staff costs, it also comes with a risk of retail theft at self-checkouts. With the circumstances the world now finds itself in i.e. mass unemployment, financial uncertainty, the retail industry has seen an influx in these types of petty crimes, hitting retailers during an already turbulent period. While retailers are taking precautions to protect themselves and their patrons in this new era of in-person shopping, it’s important to ensure the business itself is protected. A popular method to combat these fears is to employ on-site security personnel, however, as we continue to adapt to new operating guidelines, retailers must begin thinking past the immediate future, and begin implementing long-term security solutions to prepare for life after lockdown such as strong CCTV systems with remote access. How has the security industry adapted its services to a post-lockdown world? Technological innovations like thermal recognition are key to adapting security systems for a post-lockdown world. Businesses which previously relied on facial recognition now must update their methods to account for shoppers wearing masks on-site and in-store. By 2021, we’re globally on track to have 468,000 self-checkout machines in operation, nearly double the 240,000 in existence since 2016 Biometric systems are now able to identify people with face masks, and thermal recognition such ADT’s Thermi-Scan system which can track human body temperature without the need for contact. Implementing these safe protocol procedures protect both employees and customers against virus outbreaks such as COVID-19. The need for these advances in video surveillance will reportedly increase the biometric facial recognition market by 14 per cent by 2027. Artificial intelligence has been hailed recently as the way forward for remote security needs, and while business-owners continue to navigate procedures of returning to work post-lockdown, having remote access to real-time security monitoring is essential now more than ever. What are the main measures stores can take to prevent or reduce theft? Strategically placing a multi-camera surveillance system to ensure clarity, eliminate blind spots, and deter thieves should be top priority. It’s equally essential to invest in a system which has an efficient playback program, particularly in situations where reviewing important footage efficiently can offer vital information to the police force. Advances in video surveillance will reportedly increase the biometric facial recognition market by 14 per cent by 2027 As business-owners continue operating at reduced hours and with limited on-site staff, being able to access camera footage quickly and remotely is a key factor to consider. Whether owners opt to receive an alert on a mobile device allowing them to review notifications, or if their system is monitored by a remote security center, it’s important to be able to access footage quickly for added efficiency and ease. Facial recognition and AI have been popular points of discussion in relation to security cameras and CCTV. While careful considerations must be taken prior to utilising any sort of facial recognition technology, including conducting a Privacy Impact Assessment, the benefits include being provided with real-time tracking of repeat offenders which immensely helps the prevention of in-store theft. Here are some key points to consider when choosing in-store surveillance: Assess your needs – To get the best out of your security system, it is essential to analyze what your requirements are for your business as they might have changed to adapt to a post-lockdown world Camera setup – With store layouts shifting to accommodate social distancing guidelines, it’s important to re-evaluate the current set-up of any security cameras. Depending on any layout updates, it might be important to consider operating multiple cameras in one area to ensure a peripheral view and eliminate any blind spots Camera positioning – For optimal performance, check that light sources are not obstructing your view such as glare from the sun. It is also worth considering the height at which cameras are installed to maximize surveillance Check the focus – It is worth testing camera lenses bi-monthly to ensure that lighting or weather hasn’t affected the focus of the lens, resulting in a blurry visual Remote access – As guidelines continue to evolve, ensure you’re able to access any necessary camera footage quickly and safely in case of emergency Will we begin to see a reduction of theft as new technology is implemented? We’re beginning to see incidents of shoplifting and theft being taken more seriously by law enforcement. In the coming months, for the first time in Britain nearly twenty shoplifters who were either caught red-handed or identified on CCTV will be appearing before magistrates. While currently these court cases are being pursued by a private police force, these actions come after a Government plea to high-level police to prosecute shoplifters stealing under £200. Retailers have long voiced concerns that forces have abandoned low-level thefts and these steps are small but show that businesses are being heard. As innovations in surveillance security continue, we’ll be seeing a move away from human involvement which will create a more reliable and efficient system able to rely on machine learning and analytics. While there have been wider strides made in utilising AI for surveillance, these are largely being used currently by local governments to alert police forces to threats of criminal activity. It’s not unreasonable to think that in the near future, these types of smart technology will be employed by private businesses to analyze suspicious behavior or possible theft. However, as we see an increase in the advancement of security technology, we anticipate that those inclined to commit in-store theft will adapt their methods, therefore retailers should look to regularly evaluate their security needs to keep risks at bay.

Latest AxxonSoft news

AxxonSoft Announces The Launch Of The 4.4 Version Of Axxon Next Intelligent Video Management System
AxxonSoft Announces The Launch Of The 4.4 Version Of Axxon Next Intelligent Video Management System

AxxonSoft has launched version 4.4 of the Axxon Next intelligent VMS. This version includes new functions of neural analytics and camera management, enhanced GUI and Web Client, and many other enhancements and improvements. Supported body temperature measurement with a number of thermographic camera models. Measurement results appear as captions over video and are saved to an archive. Upon discovering an individual with abnormal body temperature, the camera creates an alarm event, and sends it to Axxon Next. The user can set up an auto response scenario to notify operators or responsible staff, start video recording, etc. Based on alarm events, the user can quickly find videos of individuals with elevated body temperature. Mask detection - Based on neural network algorithm for facial recognition, this tool detects the presence or absence of a mask on a face. Social distancing violation detection - Based on Behavior Analytics, close-standing people detection helps in social distancing enforcement. Along with non-contact body temperature measurement and mask detection, this function is included in a dedicated anti-pandemic solution. Video analytics The neural network analyses video and generates data on the postures of people in the FOV AI analytics - Neural tracker recognizes and tracks moving objects of a specified type, e.g., individuals or vehicles. The user can further apply Scene Analytics to recognized objects to detect their motion, stopping or lingering in an area, crossing a line, etc. Detection based on the neural tracker can be applied to complex scenes with a large amount of non-relevant detail, whereas classic motion detection would be drowned out by numerous false alarms. In a specified time interval, the neural tracker counts objects of a specified type within a pre-defined area, and generates an alarm event upon reaching/exceeding a specified limit. Posture detection The neural network analyses video and generates data on the postures of people in the FOV. This data is processed by analytical algorithms which are capable of detecting specified postures, such as crouching, man-down, shooting, or raised arms. Posture detection helps recognize potentially dangerous scenarios, such as: an individual crouched down next to an ATM could be a burglar an individual(s) in a shooting position and other(s) with raised arms - could be an armed robbery Handrail holding detection helps in labor safety enforcement at production facilities, construction sites, working at height, etc. Posture detection–based counter tracks the total number of individuals within a specified area, and notifies staff upon reaching/exceeding the pre-defined limit. Update required analytics Network hardware acceleration - Added support for neural network acceleration in NVIDIA and Intel GPUs, including Mustang-V100-MX8 (HDDL), Neural Compute Stick 2 and Intel HD Graphics Water level detection - This tool reads water level values from measurement scale video. Its output is represented in the Camera window with a color-coded level indicator and, as an option, a numerical value. The user can use water level detection to monitor levels of any liquid in any basin or container. Facial recognition - Facial recognition now operates in real-time. Use the AxxonNet cloud service to create lists of Facial Templates and synchronize them across all Servers connected to the user’s AxxonNet account. Upon detecting a face, a list-specific response scenario is launched. The user can use this option to create lists of VIP and/or unwanted visitors, and automatically notify retail and security staff on their entry. DetectorPack - Axxon Next detection tools are now grouped by type (core, AI, facial, LPR) and compiled into a separate DetectorPack module, subject to independent continuous development and delivery. This makes it possible to download and update required analytics between point releases of VMS. Axxon Next 4.4 includes DetectorPack 3.4.0. Web client The new Web Client functions include: Simultaneous search on multiple camera channels for specified faces, vehicle numbers, detection events, or time interval Criteria- (MomentQuest) and time-based (TimeSlice) search Building a motion heat map Alarms panel displays all active alarms across the Axxon domain H.265 playback is supported (in the Edge browser with hardware acceleration set to on) The user can select one of the two H.264 display modes: all frames, or I-frames only Select the default layout to be displayed after the Web Client launch The user can now group cameras, create camera lists and sort cameras within a list by their names or IDs Camera management Recording on motion from embedded VMD - When the user adds a camera to their system, they can now quickly set up motion-based recording from on-board Video Motion Detection. For each added camera, the system automatically creates a VMD tool and a rule for automated recording to the specified file. When VMD triggering ends, video recording stops. Adding links to other cameras - Users can now include links to other cameras in a camera window. Clicking a link brings the user to the linked camera. This function facilitates object tracking between different camera FOVs. User Interface Videowall Management - A video wall is a set of display monitors physically and logically connected to act as a single screen. A video wall may include any monitor connected to any Client within the Axxon domain. In Axxon Next 4.4, the users can set up a video wall via a WYSIWYG GUI: monitor images on screen now match their physical layout. User rights now include an option to manage other Clients' monitors, not only local ones. On each monitor, users can set up layouts and quickly add cameras by dragging their icons from the Objects panel (Devices tree) or interactive Map. Hot keys for video walls control were added as well. Geo Map management - The user can specify coordinates of a camera: latitude, longitude, and bearing. When they add a camera to a geo map, its icon appears in a location that corresponds to its coordinates. On the map, the user can now search geo objects by their names. These functions will be useful for large-scale and distributed systems, including Safe City projects. Temporary layout in archive mode - The user can now create a temporary layout that includes cameras selected for Archive (video footage) viewing. This is a convenient tool for simultaneous viewing of multiple camera feeds for event analysis. When another layout is selected, the temporary layout is automatically deleted. Fast access to detection triggering events - The users can now quickly access detection triggering events on any layout with the newly introduced events panel to the right of the camera window. The panel contains the list of most recent detection events from tools created for this particular camera.

Lessons Learned With AxxonSoft: How Have You Adapted To The COVID-19 Pandemic?
Lessons Learned With AxxonSoft: How Have You Adapted To The COVID-19 Pandemic?

The coronavirus pandemic has brought about an unprecedented crisis for businesses and individuals. It has also created a new normal, notwithstanding the disruption to our lives, ultimately changing life as we knew it. However, our resilience as humans will ensure that we survive and become better, stronger, and more determined than ever before. As I mentioned, both businesses and individuals have struggled significantly to balance the need for safety versus survival. But at AxxonSoft, we remain committed to keeping our people safe, while ensuring that our support and commitment to our clients are not compromised. Ensuring business continuity At AxxonSoft, our vision has always been to ensure business continuity through enhanced safety and video surveillance offerings. Adhering to the COVID-19 regulations, we are prescribing to social distancing to slow the spread of the virus. As such, we are utilising this time to ensure that our service offering is optimized to afford our clients the ability to repurpose and extend their remote working viabilities. As an essential service provider, we have ensured that we are providing the right tools to our clients to comply with regulations. Our video analytics and face recognition services have no reliance on on-site control rooms and, therefore, clients’ security solutions and personal safety are not compromised. Innovation reimagined During these precarious times, our focus remains on support and service. Our development team continues to work tirelessly to ensure that you can use our software during the lockdown and have accelerated innovation to this end. While we must maintain social distancing, we can and will still be of service to our community Therefore, we are proud to present version 4.11 of the Intellect PSIM, which offers our clients a neural network-based analytical tracker which recognises specific types of objects, such as humans and vehicles. We have also equipped this version with video wall management interface, automatic object tracking and a web reporting subsystem. Behavioral analytics generates data by detecting specific postures, like crouching, shooting or any potentially dangerous scenario. Our surveillance software operates on a three-pronged approach: calibration, detection and measurement, offering a comprehensive bird’s-eye view to clients. This upgrade also upholds mandated social distancing measures and keeps any face-to-face meetings to a minimal. The silver lining is that you can even use this technology when the pandemic is over. Now that’s what I call experiencing the next with AxxonSoft! Finding solutions to the challenges Our specialist technology and frontline technical support staff will ensure that your business is protected during and post-lockdown. We will continue to ensure that we provide solutions to the new challenges that the coronavirus brings, ensuring that our clients can emerge stronger and more responsive to any changes in the future. Our surveillance software operates on a three-pronged approach: calibration, detection and measurement While we must maintain social distancing, we can and will still be of service to our community. After all, change is not just about technology but about mastering mindsets. The COVID-19 disaster has demanded that businesses embrace tech disruptions as early as possible and apply technology in imaginative ways to define the new world of work. Until next time, stay safe!

AxxonSoft Announces Release Of Version 4.11 Of The Intellect PSIM
AxxonSoft Announces Release Of Version 4.11 Of The Intellect PSIM

AxxonSoft has announced the release of version 4.11 of the Intellect PSIM. The new version provides neural network–based analytics, video wall management interface, automatic object tracking with a PTZ camera, support for Intel Quick Sync Video hardware decoding, and servers for ONVIF and SIP protocols. The new release also includes updated versions of Face Intellect, POS Intellect, Auto Intellect, and Web Reporting subsystem, along with many other enhancements and improvements introduced. Video Analytics Neural Tracker The neural tracker uses DNN (deep neural network) to recognize specific types of objects, e.g., humans or vehicles. The neural tracker tracks objects in motion, which allows the application of any VMD-based detection tool: motion in an area, line crossing, appearance/disappearance of an object, etc. Detection based on the neural tracker can be applied to complex scenes with a large amount of non-relevant detail, whereas classic motion detection would be drowned out by false alarms. One neural tracker can work with several individually set-up counters, with various detection zones Object Counter A neural tracker can be linked to a counter that will periodically report the number of objects within a specified area in the FOV. One neural tracker can work with several individually set-up counters, with various detection zones, reporting intervals, etc. Neural Filter The neural filter works in parallel with the standard tracker, which allows the detection only of moving objects of a specified type or abandoned objects, while ignoring all other movement in the FOV. The results of their joint operation can be used by VMD-based detection tools in real time and recorded to a database that allows the quick location of objects of a specified type in recorded footage. Custom training of neural networks AxxonSoft offers custom training of the neural networks used by the neural tracker and neural filter To deliver high-quality video analytics, AxxonSoft offers custom training of the neural networks used by the neural tracker and neural filter. For each particular project, these AI tools are trained with the help of videos shot on site. Behavioral Analytics The neural network analyzes video and generates data on the postures of people in the FOV. This data is processed by analytical algorithms which are capable of detecting specified postures, such as crouching, lying prone, shooting, with hands up, or the appearance of an individual in any posture. Behavioral analytics detects potentially dangerous scenarios by specific postures, for example: An individual crouched down next to an ATM could be a burglar; One in a shooting position and other(s) with hands up could be an armed robbery. Enhanced and Optimized Added an option to save and recall templates for Forensic Search in Video Footage. A saved template can be re-used for further searches by using the same criteria. Updated neural algorithms for fire and smoke detection. Added Alarm Expired events for these detection tools, and an option to select processing hardware: GPU or CPU. Optimized memory consumption by the sweet-hearting neural detection tool that shows items not being swiped at the cash desk. Improved the stopped vehicle detection tool. Video Surveillance Added Tag&Track Pro feature that automatically tracks an object with a PTZ camera using coordinates obtained from the fixed camera's tracker. To start tracking a moving object, just click on its image. The PTZ camera will track it until the object leaves the fixed camera's FOV. Implemented support for the hardware decoding of H.264 streams using the Intel Quick Sync Video technology. The decoding is performed by an Intel GPU, which significantly reduces the Server's CPU load when applying video analytics, and the Client's CPU load when displaying video feeds. Added an option to hide selected portions of an archive. The availability of the options of hiding records and viewing hidden archives depends on the assigned user rights. One can now also mask faces on exported videos. To make it possible, the neural network automatically locates faces in recorded footage. These functions are required to comply with privacy and data protection requirements, such as the GDPR. Added an option to export videos from external storage, such as IP camera archives or NVRs. Added a comprehensive set of system events to audit operator's actions. Communication Protocols ONVIF Server - The ONVIF server is used for media streaming to external systems. It allows ONVIF clients to connect to an operating Intellect PSIM system, as they would to an ONVIF compatible device. Supported video streaming with synchronized audio in H.264/H.265/MPEG-4/MJPEG formats, multi-streaming, access to Video Footage, multicasting, authentication, and transmission of I/O events from devices and metadata. SIP Server - The SIP server allows the Intellect PSIM to connect to intercom devices such as IP door stations and push plates, and to create and route calls. The server supports audio and video calls, which can be recorded for further monitoring. Security system operators can now communicate via a new SIP Panel client interface. Each device and SIP Panel is assigned a calling ID number, and address books containing available call numbers are set up on SIP Panels. Other Protocols - Added support for the AMQP open messaging protocol, which allows the Intellect PSIM to receive and send RabbitMQ messages. Implemented the HTTP Server module, which is capable of sending events to an external system via HTTP polling. The User Interface Screen Manager Screen Manager is a new UI for video wall management. It enables convenient monitor layout management on selected PCs. Screen Manager can be used to: Create, edit, or delete layouts, and assign them to selected PCs; Remotely switch layouts on PCs. Operator Protocol For objects linked to a camera, they can now display a still image or recorded video of an event Operator Protocol is now completely revamped. Events list is now displayed as tiles, sortable by time and priority. Events processed by other operators are marked with a gray background, and their cells include the name of the Operator Protocol in which the processing has been completed. Users can now escalate an event to a specified operator. The parameters displayed along with the event are now selectable. For objects linked to a camera, they can now display a still image or recorded video of an event and zoom in on the alarm snapshot in a separate window. If an object is linked to multiple cameras, users can scroll between their images and can set video display in the Camera Window or ActiveX component. Set Bookmark checkbox All buttons and comments are now located on a single upper panel. An operator can now select several events, and work with them simultaneously. Another new feature added is a Set Bookmark checkbox for automatic creation of a bookmark in Video Footage when an event is processed by the operator. Operator's text comments are used for bookmark names. Incident management Additionally, a new feature added is the incident management function. If an operator selects an event, a list of required processing actions is displayed. The operator selects the required checkboxes, and information about their actions is added to text comments along with date/time stamps. In addition, the operator can now view processing instructions for events from any source object. Other new interfaces and enhancements The object context menu on the Map now includes an option to set the number of recent events to be displayed (up to 99). Introduced an option to request single frames or camera archives (also for cameras under a parent object) via the ActiveX component. The Main Control panel now includes the following information about the system - product name and version, installed subsystems' names and versions, available system objects list and the number of used objects, and license expiration date. Also added is a new graphs interface containing analog sensor data representations, and an interface allowing display of statistical data about objects' statuses as a table or a chart. User Rights Added support for Active Directory service, which enables synchronization between users and groups of the Intellect PSIM and their relevant Active Directory objects. When creating a new user rights group, operators can now import settings from an existing group. If multiple groups are selected, their combination is created. Added a setting to automatically shut down the session if the operator becomes idle. Added an option to limit the list of available actions on objects in video surveillance monitor and Map UIs. Added an option to disable frame/video export and printing a still frame from the video surveillance monitor. Auto Intellect 5.5 Introduced a module that uses the neural network to detect vehicle types. The module is capable of classifying passenger cars, vans, buses, trucks, and motorcycles. Integrated the IntLab container number recognition module. Updated the IntelliVision car number recognition module. Added support for new national license plate formats and running recognition on GPU and increased overall recognition quality. Basic virtual loop is now replaced with the IntelliVision virtual loop. The SDK for the AutoUragan LPR module is updated to version 3.7. Added new national formats and templates and increased operational stability. Updated VIT LPR module to version 2.7.2. Added new national formats and templates, increased recognition quality and stability; the GUI now includes tools for fine-tuning the module. Face Intellect 7.3 Integrated new YITU and SCT facial recognition modules. Updated VisionLabs facial recognition module to version 3.6.3. In the Tevian engine, recognition of emotion, race, and facial attributes (glasses, mustache, beard, hair color, headwear, etc.) was added to the existing age and gender guesstimation capabilities. Facial recognition now warns of faces covered with masks etc. and performs "liveness" checks to preclude identity spoofing. Operators can now use facial attributes for filtering, e.g., to find all males wearing glasses and/or with a beard. Emotion recognition allows you to evaluate the quality of personnel operations and the degree of customer satisfaction in banking, retail, and other industries. The Face Search tab now includes filters by name, department, and similarity rate, time window presets, and saving search parameters (filters) option. Operators can now launch a filtered search by double clicking a facial image in the captured/recognized faces log. Other new features: The full names of recognized persons now appear on live video under the facial bounding box; Users can now check an entire folder containing facial images against your DB; Facial recognition now has a configurable capture area; Facial DB replication across servers now allows a face to be added to all DBs by adding it to just one database. POS Intellect 5.4 Integration of the screening system allows data to be received from connected devices Integrated 5 models of POS terminals, 2 models of vehicle scales, a printer scales and the Sphinx screening management system that supports up to 5 handheld metal or metal/radiation detectors. The integration of the screening system allows data to be received from connected devices, recorded to the POS Intellect DB, used for captioning screening videos, and utilized for searching by text comments in Video Footage. The integrated solution allows one to control equipment and personnel operations for more efficient and reliable screening. In POS Intellect, existing integrations have been enhanced, and the wildcard search in captions has been introduced. Intellect Web Report System 3.4 The web report subsystem now includes new and updated reports, and new functions have been introduced. New Types of POS Reports - A "sweet-hearting" report allows one to view event video live. A canceled items report contains data filtered by specified cashiers and item names over a specified period. A canceled amount report is similar to the one previously listed and includes the total value of canceled items. New Types of Time and Attendance Reports A consolidated employees report contains data on the total number of employees in specified departments, and the number of employees staying in a specified area at the moment of reporting, or on a specified time/date. A detailed employees report contains data on the number of employees staying in a specified area during each day of a specified time period. Other New Report Types - A customer counter report contains information about the number of visitors who entered/exited a specified area over a specified period and is presented as a graph or as a table. A graphical report on events represents the number of events of a specified type for the selected types of objects over a specified time period. The exported report includes both a graph and a table. A pass card report contains information about the times of issuing pass cards for specified employees, or departments, as well as the types of cards and their expiration dates. A recognized rail car numbers report contains information about error detection with a check digit and a photo from the linked camera.

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