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On September 8, Johnson Controls, the global pioneer for smart, healthy, and sustainable buildings, kicked off its 2021 ‘Game On’ Roadshow in Milwaukee, Wis. where almost 60 attendees participated in hands-on learning experiences with commercial HVAC rooftop units from Johnson Controls, YORK®, and TempMaster®.

The roadshow tour brings the comprehensive and newly extended rooftop unit portfolio to locations across the U.S., including Chicago, Denver, and Phoenix, among others.

Displaying commercial units

As part of the tour, the 53-foot ‘Game On’ trailer houses full-size displays of the Choice 15-27.5 ton and Select 27.5-50 ton commercial rooftop units to give visitors hands-on interactions with the equipment.

The agenda includes engaging, interactive experiences, featuring the Premier 25-80 ton rooftop units

The agenda also includes engaging, interactive experiences, including augmented reality, featuring the Premier 25-80 ton rooftop units, variable air volume (VAV) products, and the Verasys® building controls system – all part of Johnson Controls connect suite of OpenBlue technologies.

Providing hands-on product experience

The ‘Game On’ Roadshow is an immersive, mixed-use experience that brings cutting-edge Johnson Controls, YORK®, and TempMaster® products directly to our customers in a meaningful way and provides hands-on opportunities to learn about the latest technologies and innovations,” said Doug Schuster, vice president, and general manager, Ducted Systems, Johnson Controls. “This is the culmination of years of planning and hard work to show our customers that Johnson Controls is here to help them win.”

With events held in nearly 20 states, the ‘Game On’ Roadshow is part of Johnson Controls' overall commitment to customer success and innovation, including the expansion of the company’s state-of-the-art 900,000 square-foot Rooftop Centre of Excellence manufacturing facility in Norman, Okla.

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The EU called for a ban on police use of facial recognition but not commercial use. Why?
The EU called for a ban on police use of facial recognition but not commercial use. Why?

Recently, the European Parliament called for a ban on police use of facial recognition. In the US, too, some cities have restricted police use of facial recognition. The first question that comes to mind is - why ban police from using technology that is allowed to private companies? Point of difference The key difference between the way police use facial recognition and the way commercial facial recognition products work is that: The police get a picture of a suspect from a crime scene and want to find out: "Who is the person in the picture?" That requires as wide a database as possible. Optimally - photos and identities of all the people in the world. Commercial facial recognition products such as those used by supermarkets, football stadiums, or casinos answer different questions: "Is the person in the picture on the employees' list? Is the person in the picture on a watch-list of known shoplifters?" To answer these questions doesn't require a broad database but rather a defined list of employees or a watch-list of specific people against whom there is an arrest warrant or a restraining order. Use of facial recognition AnyVision helps organisations leverage facial recognition ethically to identify known persons of interest "Facial Recognition Apps Should Be Provided to the Police with an Empty Database". This is exactly the subject of the open letter sent by AnyVision, to the British Biometrics and Surveillance Camera Commissioner, Prof. Fraser Sampson, titled: "Facial Recognition Apps Should Be Provided to the Police with an Empty Database". AnyVision recently raised $235M from Softbank and another leading VCs is a visual AI platform company that helps organisations across the globe leverage facial recognition ethically to identify known persons of interest, including shoplifters, felons, and security threats. Ethical use of facial recognition AnyVision CEO Avi Golan wrote, "The ethical use of facial recognition is a thorny one and requires a nuanced discussion. Part of that discussion has to explain how facial recognition works, but, just as important, the discussion must also involve how the technology is used by police departments and what checks and balances are built into their processes.” “We recommend building their watchlists from the ground up based on known felons, persons of interest, and missing persons. Some facial recognition solution providers have scrapped billions of photos and identities of people from social networks, usually without their consent." "Unfortunately, this method of facial recognition has justifiably angered privacy groups and data protection agencies around the globe and damaged the public trust in accuracy and reliability of facial recognition systems.” Preventing invasion of citizen’s privacy We believe an unjustified invasion of citizens' privacy can be prevented, false arrests can be reduced" “We believe that lists of suspects should be limited and justified. In this way, unjustified invasion of citizens' privacy can be prevented, false arrests can be reduced and public confidence in technology can be increased.” Golan added: "AnyVision is willing to share its industry insights and best practices from our vast research experience with leading global players, including name-brand retailers, global hospitality and entertainment companies, and law enforcement agencies from around the world.” Balancing public order and crime prevention “If the regulations set forth by Surveillance Camera Code of Practice are committed to the principles outlined above, then law enforcement agencies can strike the right balance between the need to maintain public order and prevent crime with the rights of every person to privacy and non-discrimination before the law." Recently Clearview AI CEO told Wired; the company has scraped 10 billion photos from the web - 3 times more than was previously known.

Dahua Technology shows how intelligent cameras enhance safety in nursing homes
Dahua Technology shows how intelligent cameras enhance safety in nursing homes

Patient falls in nursing homes are a serious problem. In the United States, for example, around 1,800 elderly people, living in nursing facilities, die each year from injuries related to falls, according to the Nursing Home Abuse Center. Those patients who survive their injuries often have a reduced quality of life and suffer some form of permanent disability. Rise in nursing home patient falls Figures show that between 50% and 75% of nursing home residents suffer falls each year, twice the chances of falling when compared to seniors who live in a regular residential community. It has been a prevalent challenge to detect falls quickly and effectively, especially when these occur in residents’ bedrooms. In the United Kingdom, the Care Quality Commission has recognised that the use of CCTV may be one of the best ways to ensure safety and quality of care. However, using video surveillance also brings into question other security issues, such as privacy and data protection. Dahua’s WizMind technologies WizMind embraces human-based AI (Artificial Intelligence), for a whole host of applications across verticals This is where Dahua Technology’s WizMind technologies come into play. WizMind embraces human-based AI (Artificial Intelligence), for a whole host of applications across verticals, such as retail, energy, finance, transportation and of course, health and social care. Specific to the health and social care sector are deep-learning algorithms, to protect the privacy of the face and body in real-time, and stereo analysis, which combines dual-lens cameras with three-dimensional scene analysis, in order to detect sudden physical movement, such as falls. Stereo video analysis The growth of AI applications has enabled the greater availability of 3D scene analysis solutions, thereby enabling objects and people to be analysed in three dimensions. Dahua Technology’s stereo analysis uses two lenses, in order to capture separate images of the same scene. It then computes the ‘optical parallax’ of spatial points in the two images, providing 3D information of the scene. The stereo vision mimics the depth of view that comes from humans having two eyes, known as binocular vision. Combined with deep-learning algorithm Combined with a deep-learning algorithm, stereo analysis can recognise event patterns, such as falls and other movement-based behaviours, such as people approaching, the detection of an abnormal number of people in an area, and violent behaviour. In nursing and care homes, stereo analysis cameras can help staff monitor residents, in case of emergency and respond to residents’ problems, such as tripping and falls. The cameras can view all three dimensions of subjects and together with its deep-learning algorithm, can immediately alert staff to any unusual or sudden movement, such as would be evident in a fall. Cameras in communal areas and bedrooms With cameras situated both in communal areas and in bedrooms, the staff is able to respond quickly to incidents With cameras situated both in communal areas and in bedrooms, the staff is able to respond quickly to incidents, which may otherwise stay undiscovered for hours. An example of such a scenario is a nursing home in Singapore, which has a capacity of around 400 beds and is divided into 14 separate living environments, with each designed to be a home-like living area. Dahua cameras with intelligent fall detection technology Dahua cameras, such as IPC-HDW8341X-BV-3D with intelligent fall detection technology were installed, including the provision of 167 stereo analysis cameras inside each bedroom. These trigger an alarm, in the case of incidents, such as a fall, allowing immediate response by staff. Not only does this enhance the well-being and safety of residents, but it also can reduce the nursing home’s labour costs. In addition, Stereo Analysis can also be applied in other application scenarios. An underground unmanned bicycle parking garage in Amsterdam, for instance, has installed Dahua Technology’s behaviour analysis cameras, to detect abnormal events and prevent accidents, such as people tripping and falling, or suspicious individuals wandering around the area. Privacy Protection 2.0 technology While monitoring their situation inside the nursing home, Dahua also adopts Privacy Protection 2.0 technology that features masking of human face and body, to protect the residents’ privacy. It involves the restriction of what can be seen in video images and applies equally to live, and recorded images. Digital masking takes place on the front-end device (e.g. network camera). Dahua’s Privacy Protection 2.0 provides real-time occlusion of the body and face and enables users to access recorded videos, without having to overlay faces with mosaic masks. It also offers additional occlusion options, such as irregular polygons, mosaics and coloured blocks, and allows code exporting based on specified targets, ensuring the privacy of subjects. Privacy and security in evidence collection Stereo video analysis and privacy protection come into their own in nursing homes and healthcare facilities Benefits offered include non-pixelated human targets, allowing for privacy and security in evidence collection. The technology also allows for face and human attributes analysis, without breaching people’s privacy, making it ideal for nursing homes. Stereo video analysis and privacy protection come into their own in nursing homes and healthcare facilities. It allows the close monitoring of residents or patients to help ensure their well-being and safety, while at the same time protecting the privacy of often vulnerable individuals. Dahua TechMonth As part of the Dahua TechMonth, this blog highlights how Dahua’s stereo analysis technology, combined with privacy protection, can provide a valuable tool to help staff respond to incidents quickly and efficiently, including falls, without infringing on people’s data protection rights. In the next blog, Dahua Technology will be discussing the WizMind application of human metadata, enabling users to maximise situational awareness and analysis of events. 

Eagle Eye’s Uncanny Vision deal highlights value of combining AI and cloud
Eagle Eye’s Uncanny Vision deal highlights value of combining AI and cloud

The trend of video customers moving to the cloud has reached a tipping point. At the same time, artificial intelligence (AI) is being adopted on a massive scale. Combining the two trends adds a higher level of value than either component individually. Merging the power of AI and the cloud is a driving force behind cloud surveillance company Eagle Eye Networks’ acquisition of Uncanny Vision, an AI and video analytics company headquartered in Bangalore, India. Expensive AI resources Cloud systems empower customers to leverage AI without having to install and program complicated and expensive hardware, in effect stripping away the barriers to entry that customers face when seeking to embrace AI. The cloud also enables customers to share expensive AI resources. One of the key components is ease of deployment – click, click and turn on the AI for any camera" Simplicity of implementation is crucial to the combined value proposition of Eagle Eye Networks and Uncanny Vision. “One of the key components is ease of deployment – click, click and turn on the AI for any camera (in a cloud system),” says Dean Drako, Eagle Eye Networks CEO. There is also a benefit of having AI systems networked, enabling 25 banks to perform facial recognition of customers from a single cloud-based system, he adds. A transition is also under way in the perception of AI. Video surveillance applications While previously it was seen as an add-on to surveillance systems, now it is seen as a very desirable feature on any system. “Centralised management of the cloud benefits the AI database,” says Drako. “In a project built around licence plate recognition (LPR), for example, all the data goes up to the cloud into a single database, and the customer can get a mobile view of everything going on across the world. You can’t do that without the cloud. And AI for LPR is more accurate.” Uncanny Vision’s targeted focus on AI for video surveillance applications was one factor that attracted Eagle Eye Networks to make the acquisition, says Drako. In contrast, some other companies have embraced broader applications of video AI. Uncanny Vision also has more customers using their system in real-world applications than competitors. Finally, the acquisition will help to expand Eagle Eye Networks’ presence in the LPR market, where Uncanny Vision is especially strong. Improving business operations The 60 employees at Uncanny Vision are mostly engineers and programmers Uncanny Vision’s deep learning algorithms enable recognition, identification, and prediction, improving business operations, customer service, and site safety. Applications include smart parking, retail, smart cities, ATM monitoring, worker safety and perimeter security. The 60 employees at Uncanny Vision are mostly engineers and programmers. “These guys understand how to translate AI algorithms to run very efficiently on various types of hardware,” says Drako. “They optimise how they get the code to run so we can implement in the cloud cost-effectively. They do it at a modest cost to make it more accessible. They understand how to deploy software for high performance on low-cost hardware.” For Uncanny Vision, the new ownership provides more reach. “We have a huge channel and a huge brand,” says Drako. “They are strong technical guys who need a sales and solution channel.” Video analytics solutions Even in light of the acquisition, Eagle Eye Networks will continue to provide a selection of third-party AI and video analytics solutions to customers. Use of AI and video analytics is specific to the application and business needs of each customer. Use of AI and video analytics is specific to the application and business needs of each customer In addition to AI functionality, systems need a ‘business logic’ component that drives how that capability is integrated into a system. System needs vary widely by vertical market, and many third-party vendors are focused on a specific vertical and how AI can benefit that market. Recurring monthly revenue “Third parties can provide analytics and the business logic, which is different for a factory, an office building or for a drive-thru restaurant,” says Drako. “The market is looking for many solutions, and one company couldn’t own a majority of them.” To ensure flexibility, Eagle Eye Networks will accommodate third party solutions, deploy their own analytics, or leverage analytics embedded in cameras. For Eagle Eye Networks’ dealer and integrator customers, the expansion into AI presents a new opportunity for recurring monthly revenue (RMR) and provides greater value to customers. Drako says the impact of the acquisition will be global as AI applications grow in popularity worldwide.