Digi Video Motion Detectors

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.  

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.

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.