IndigoVision Video Surveillance software(7)
IndigoVision, leading manufacturer of IP video security solutions, has established itself as one of the most open surveillance systems on the market with the latest release of its SMS4™ software. SMS4™ release 5 includes Camera Gateway™, which allows IP cameras from top manufacturers to be integrated into the IndigoVision SMS4™ system, making it easy to upgrade a client’s existing IP-CCTV system to a quality IndigoVision solution. Camera Gateway™ enables cameras from a range of other manufacturers to be connected to an IndigoVision SMS4™ system using their native protocols and enables users to view the cameras in IndigoVision’s Control Center. The cameras can be controlled, viewed and recorded in the same way as IndigoVision cameras. Camera Gateway™ also supports PTZ control, bookmarking and record-on-motion. Camera Gateway™ is a software service that can be installed on a Windows based server, giving customers total flexibility. The service enables multiple clients to stream and view video from the same camera. Marcus Kneen, IndigoVision CEO, stated: “Camera Gateway™ is a game-changing product making IndigoVision SMS4™ the open system of choice. Combined with our conformance to the ONVIF standard, and our integration with other software, SMS4™ release 5 establishes IndigoVision as one of the most open IP security solutions on the market.” SMS4™release 5 also includes record-on-motion and bookmarking for IndigoVision’s own cameras and those of supported manufacturers. Record-on-motion allows users to reduce storage by configuring the system to record video only when there is activity, while bookmarking video footage makes it easier to find and review key evidence. Users can upgrade to SMS4™ release 5 through IndigoVision’s Software Upgrade Program (SUP).Add to Compare
IndigoVision, the leading manufacturer of complete end-to-end IP security solutions, has released Video Wall software that allows professional fully-featured IP-CCTV control room video walls to be built to any size, at a fraction of the cost of other dedicated display products. Based on ‘Control Center', the company's Security Management Software, video walls can be constructed with complete scalability using any PC monitor type (CRT, LCD and plasma), with standard or High Definition wide-screen format. The video wall is driven using slave ‘Control Center' workstations, each of which manages up to 4 monitors. Up to 98 slaves can be controlled over the IP network from an unlimited number of master ‘Control Center' workstations. Each monitor can display up to 25 video panes, allowing video walls with up to 9,800 panes to be constructed. On large sites multiple video walls can be deployed in different control rooms, all accessing the same video from any camera or Network Video Recorder (NVR), no matter where they are located. This can only be achieved because IndigoVision's architecture is completely distributed. Monitors within the video wall can be used to display a variety of information, including live or recorded video, guard tours, salvos, site maps and alarm status. In addition, information from third-party applications can be displayed, such as the status of access control or building management systems. The video wall is controlled using standard CCTV keyboards connected to any of the master workstations. The video wall supports the ‘Control Center' black screen monitoring mode, where video is only displayed on alarm. This method of operation is recognized as providing a more efficient operator environment that leads to quicker incident response. Using IndigoVision's advanced alarm management features, content and layout of individual monitors in the video wall can be controlled dynamically from the status of alarms and events.Add to Compare
IndigoVision recently released new software to coordinate responses between agencies and operatives with pervasive real time video. The system automatically validates incoming data to verify critical events, escalating video for management of the situation to personnel in other locations and ensuring an appropriate response. Operatives are provided with both real time and recorded video, giving them the ‘eyes and ears everywhere' to optimally assess the situation. IndigoVision's SMS4 release 3 starts with the qualification of incoming data to filter out false alerts so personnel can focus on likely threats. The system also lets you embed prior intelligence by noting the sequence and combination of events that may constitute a situation. Qualified alerts that are not assessed within a certain time period are then automatically passed along a chain of operators, accompanied by real time contextual video, to guarantee a swift response. Events that are identified as priority get automatically escalated to higher levels of authority and/or agencies in other locations. SMS4 release 3 also supports the automatic expansion of the 'threat zone' if the initial situation is not handled within a certain time. For example, if a perimeter breach is not addressed quickly, then nearby buildings are automatically placed into alert. The new analytics added to this latest release allow operators to filter situational data by location, zone or incident criteria to better understand how events unfolded. Automatic scheduling of actions based upon time of day and other criteria can also be developed into ‘routine scenarios', which will receive an automated but intelligent response. Another new feature is the addition of ‘audio forensics', which greatly improves investigators' abilities to locate critical evidence fast. The addition of audible data such as a breaking window to existing video forensics can aid police officers and other emergency personnel to get straight to the action. SMS4 release 3 is the latest evolution of IndigoVision's leading edge security management software. With enhanced capabilities for managing multi-agency situations through pervasive access to video, SMS4 release 3 empowers its users to greatly increase their response time and accuracy. Existing users can upgrade to SMS4 r3 through IndigoVision's Software Upgrade Program (SUP).Add to Compare
IndigoVision has developed a powerful surveillance solution for the retail and hospitality sectors by integrating its IP Video system with Electronic Point of Sale (EPOS).Data sent from an EPOS system can be overlaid on a live video display, allowing operators to view the camera feed and till transaction simultaneously. The transaction information and alarms generated by the EPOS system are also bookmarked and recorded alongside the video. This facilitates visual identification of an incident in both real time and through post-event analysis.Powerful transaction analysis can be undertaken on the stored data, for example, finding out when a particular credit card was used by searching every till in a store or across all stores from the head office. Conversely, recorded video can be searched using a thumbnail feature, which displays a video still image for every transaction, allowing the operator to quickly identify the relevant footage. Evidential quality video clips and associated transaction data can be exported for investigation or use in court. This can be played back using IndigoVision's standalone Incident Player.Alarms generated by the EPOS system, such as ‘till left open', ‘refund', or ‘large note deposit' can automatically trigger a number of events. For example, display the nearest camera view to the specific till and pinpoint the alarm on an interactive map. This creates a more efficient operator environment that leads to quicker incident response. Alarms from non-security systems such as building management and plant monitoring can also easily be integrated into the system and benefit retail applications, for example, alerting staff when a freezer fails or a door is left open."IndigoVision has a strong presence in the retail sector and has deployed surveillance systems with some of the world's best-known retailers such as IKEA, Sears and John Lewis Partnership," said Oliver Vellacott, IndigoVision CEO. "This new development will strengthen that position further and provide stores with an unmatched solution for integrated surveillance."The seamless integration with third-party systems is achieved through integration modules in ‘Control Center', IndigoVision's Security Management Software. In addition to EPOS, the company has integration modules for over 20 different IP-based access control and security systems.Add to Compare
IndigoVision’s analytics algorithms run both in real-time on live video and also on recorded video using ‘Control Center’, IndigoVision’s enterprise video and alarm management software. Real time analytics are located at the edge of the network, i.e. at the camera, making the solution totally scalable. CCTV operators can now detect events as they happen such as congestion, stolen objects, cars parked too long outside a building, people moving the wrong way through security checkpoints, etc. Live demonstrations of the new advanced analytics suite will be available throughout the Security ESSEN show. IndigoVision’s new analytics include: Congestion Detection Motion DetectionAbandoned Object DetectionCounter FlowVirtual TripwireShape-Based DetectionObject Tracking and Theft DetectionAll of these can be run in real-time at the camera or post-event on recorded video. Real time analytics run in the 8000 Transmitters connected to analog cameras and in IndigoVision’s dedicated high-end IP domes. This significantly reduces bandwidth requirements on the network and ensures the system is totally scalable. Pre-determined events are identified as they happen, at any camera, and can drive the virtual matrix, e.g. display a salvo on a bank of monitors. Real-time analytics lead to increased effectiveness and improvements in incident detection hit rates. Using ‘Control Center’ software, recorded footage stored on IndigoVision’s networked video recorders (NVRs) can be analysed using the same algorithms. Post processing allows operators to run many different scenarios on recorded video, e.g. look for cars parked for a certain time.Add to Compare
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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.
School shootings are a high-profile reminder of the need for the highest levels of security at our schools and education facilities. Increasingly, a remedy to boost the security at schools is to use more technology. However, no technology is a panacea, and ongoing violence and other threats at our schools suggest some level of failure. We asked this week’s Expert Panel Roundtable: How have security solutions failed our schools and what is the solution?
There was a time when men dominated the physical security industry. On second thought, that time is today. Even with increasing numbers of women entering our community, it’s an industry that is still mostly populated by men. But change is coming, and the industry as a whole is benefiting greatly from a surge in female voices. We asked this week’s Expert Panel Roundtable: What is the changing role of women in security?
Artificial Intelligence. You’ve heard the words in just about every facet of our lives, just two words, and they’re quite possibly the most moving, life-changing words employed in everyday conversations. So what exactly is AI, who currently uses it and should be using it? What Is AI? AI is a powerful way of collecting, qualifying and quantifying data toward a meaningful conclusion to help us reach decisions more quickly or automate processes which could be considered mundane or repetitive. AI in its previous state was known as “machine learning” or “machine processing” which has evolved into “deep learning” or, here in the present, Artificial Intelligence. AI as it applies to the security and surveillance industry provides us the ability to discover and process meaningful information more quickly than at any other time in modern history. Flashback - VCR tapes, blurred images, fast-forward, rewind and repeat. This process became digital, though continued to be very time-consuming. Today’s surveillance video management systems have automated many of these processes with features like “museum search” seeking an object removed from a camera view or “motion detection” to create alerts when objects move through a selected viewpoint. These features are often confused with AI, and are really supportive analytics of the Artificial Intelligence, not AI themselves. Machine Learning Fully appreciating AI means employment of a machine or series of machines to collect, process and produce information obtained from basic video features or analytics. What the machines learn depends on what is asked of them. The truth is, the only way the AI can become meaningful is if there is enough information learned to provide the results desired. If there isn’t enough info, then we must dig deeper for information or learn more, properly described as “deep-learning” AI. Translated, this means that we need to learn more on a deeper level in order to obtain the collaborative combined information necessary to produce the desired result. Deep Learning AI Deep learning AI can afford us the ability to understand more about person characteristic traits & behaviors. Applying this information can then further be applied to understand how to interpret patterns of behavior with the end goal of predictable behavior. This prediction requires some degree of human interpretation so that we are able to position ourselves to disrupt patterns of negative behavior or simply look for persons of interest based on these patterns of behavior. These same patterns evolve into intelligence which over time increases the machine’s ability to more accurately predict patterns that could allow for actions to be taken as a result. This intelligence which is now actionable could translate to life safety such as stopping a production manufacturing process, if a person were to move into an area where they shouldn’t be which might put them in danger. Useful Applications Of Intelligence Informative knowledge or intelligence gathered could be useful in retail applications as well by simply collecting traffic patterns as patrons enter a showroom. This is often displayed in the form of heat mapping of the most commonly traveled paths or determining choke points that detract from a shopper’s experience within the retail establishment. It could also mean relocating signage to more heavily traveled foot-paths to gain the highest possible exposure to communicating a sale or similar notice, perhaps lending itself to driving higher interest to a sale or product capability. Some of this signage or direction could even translate to increased revenues by realigning the customer engagement and purchasing points. Actionable Intelligence From a surveillance perspective, AI could be retranslated to actionable intelligence by providing behavioral data to allow law enforcement to engage individuals with malicious intent earlier, thus preventing crimes in whole or in part based on previously learned data. The data collection points now begin to depart from a more benign, passive role into an actionable role. As a result, new questions are being asked regarding the cameras intended purpose or role of its viewpoint such as detection, observation, recognition or identification. Detecting Human Presence By way of example, a camera or data collector may need to detect human presence, as well as positively identify who the person is. So the analytic trip line is crossed or motion box activated or counter-flow is detected which then creates an alert for a guard or observer to take action. Further up the food chain, a supervisor is also notified and the facial characteristics are captured. These remain camera analytics, but now we feed this collected facial information to a graphic processing unit (GPU) which could be employed to compare captured characteristics with pre-loaded facial characteristics. When the two sources are compared and a match produced, an alert could be generated which results in an intervention or other similar action with the effort of preventing a further action. This process- detect, disrupt, deter or detain could be considered life-saving by predictably displaying possible outcomes in advance of the intended actions. The next level is deep-learning AI which employs the same characteristics to determine where else within the CCTV ecosystem the individual may have been previously by comparatively analyzing other collected video data. This becomes deep-learning AI when the GPU machine is able to learn from user-tagged positive identification, which the machine learns and begins to further reprocess its own data to further understand where else the person of interest (POI) may have existed on the ecosystem and more correctly improve its own predictive capabilities, thus becoming faster at displaying alerts and better at the discovery of previously archived video data. The Future In conclusion, the future of these “predictables” wholly rests in the hands of the purchasing end-user. Our job is to help everyone understand the capabilities and theirs is to continue to make the investment so that the research perpetuates upon itself. Just think where we’d be if purchasers didn’t invest in the smartphone?
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