IoT solutions provider Dahua Technology releases WizSense for end-to-end solutions based on deep learning

26 Feb 2020

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Similar to the famous saying of Georges Clemenceau (“Father Victory”) that ”War is too serious a business to be left to generals”, the security matter nowadays is too serious to be entrusted to security guards, police or any personnel alone. The complexity of situations is well beyond the capacity of human eyes and brain, making modern technologies like AI suitable to play an essential role in the field work.

As is seen in the recent case of Novel Coronavirus (COVID-19) for example, thermal imaging technology is widely used in transportation hubs across China to detect possible carriers of the virus in a crowd with an accuracy of±0.3℃. AI technology will be used after to trace back their routes and locate the people they had close contact with, who will then be quarantined for at least 14 days to see if they have been infected.

Artificial Intelligence in the security industry

WizSense, a series of AI products and complete end-to-end solutions based on deep learningThe necessity of AI in security industry is also testified by the numbers that reflect people’s high expectation. According to a report by MarketsandMarkets, AI-powered Video Analytics Market is projected to register a CAGR of 41.76% during the period 2018-2022.

To accelerate AI adoption, Dahua Technology - a video-centric smart IoT solution and service provider - is proud to release WizSense, a series of AI products and complete end-to-end solutions based on deep learning that focuses on human and vehicle, providing intelligence, simplicity and inclusivity to users.

Cyber security using encryption algorithms

With easy configuration and reasonable price, WizSense is competent enough to meet the needs of most ordinary users. Its benefits include: accurate prediction before an event; instant deterrence during an event; quick target search after an event; storage saving while ensuring target details, and privacy protection and defense against attacks.

While offering abundant functionalities, WizSense also ensures high-level of cyber security using encryption algorithms that are certified by TÜV Rheinland and UL (Underwriters Laboratories). Users can rest assured that their privacy will be properly protected using WizSense series products. WizSense provides users with comprehensive protection as well as personal options to satisfy more diversified needs.

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The future of accommodation: when coliving and PropTech combine

As technology develops at an ever-faster rate, the possibilities for where and how new innovations can be used are endless. The property sector is one such area where new technology, such as smarter video surveillance, is being used to improve the quality of life for families and communities by increasing security as well as implementing changes based on new insights. Specifically for the coliving movement, cloud-based video surveillance is helping operators to improve the communal spaces for their tenants in ways that on-premises surveillance never could. From tighter security measures to better social spaces, here’s how coliving is benefitting from the PropTech (property technology) boom. What is coliving? The coliving movement is the latest iteration of a recurring human trend. The act of communally sharing space and resources while benefiting from a supportive community is something we’ve seen time and again throughout history. A place that everyone can call home addresses multiple needs. With the concept of shared spaces, and the possibility to work and socialise together, it’s no longer simply a trend. Specifically for the coliving movement, cloud-based video surveillance is helping operators to improve the communal spaces for their tenants in ways that on-premises surveillance never could. As living expenses become ever higher, for many – particularly younger – people getting on the property ladder is difficult, and renting an apartment alone can feel isolating. Coliving spaces offer a ready-built community, and many responsibilities – like maintenance, for example – lie with the building owners, and the cost is included. Where does PropTech come in? PropTech is dramatically changing the way people research, rent, buy, sell and manage property. The combination of the internet, huge compute power, cloud platforms and artificial intelligence (AI) have all combined to create technologies that are transforming the way the entire property sector works. Whether that’s helping buildings to operate more efficiently or even become more sustainable, PropTech is a sector that’s on the rise. When it comes to coliving, PropTech is helping to make these environments safer and smarter for the people who live there. One of the fundamental areas of building design is people’s safety. Following the past year where health has been at the forefront of everyone’s minds, PropTech is enabling entrance systems with touchless doorways and innovative ventilation systems, for example. And even without taking the pandemic into consideration, people living in shared spaces need to be confident that the security is well-managed, and the management wants to ensure that only tenants and their guests can enter the premises. How cloud video surveillance drives better coliving Once seen as an ‘add-on’ to building design, video surveillance and access control are now becoming increasingly important elements of the PropTech movement, and they are equally as desirable for coliving too. Surveillance cameras are essentially sensors that can monitor activity, patterns, and any other changes in a given environment. Analysis of video data can occur in real-time to effect changes immediately, or video can be stored and evaluated at a later date. In a coliving environment, a cloud-based video surveillance system can help operators to understand how tenants use their space, and implement changes to benefit them. Traditionally, video surveillance data stored on-premises had limited uses, as it was often only accessed after a security incident, such as a break-in. The video therefore wouldn’t be used frequently and the camera and storage system would just be another cost not yielding any ROI. Cloud technology has had a dramatic impact on video surveillance. Remote management delivers the ability to modify, adjust and perfect the system without needing to be present at the site, while remote monitoring alerts operators to any unusual incidents such as an equipment malfunction or breakage. In a coliving environment, a cloud-based video surveillance system can help operators to understand how tenants use their space, and implement changes to benefit them. For example, surveillance can show operators which areas in the communal spaces are frequented the most and at what times, including areas such as the laundry room or gym where space might be limited. By using AI to analyse the video, operators can use insights from it to improve the existing set up wherever possible, and also learn lessons about how to better design future co-living spaces. In today’s world, this technology can also help to keep everyone safe and healthy. Cameras can identify if someone is wearing a face mask as they go to enter a building and deny entry until they put one on. Thermal cameras are another easy tool to screen people for an elevated temperature before they even enter a communal space. Though a raised temperature does not mean you have COVID-19, the technology can provide an initial screening, so that individuals with elevated temperature readings can be checked manually for other symptoms or possibly be recommended for a test. The future of smart living Coliving is not a new phenomenon – humans have been living in communal places for many years, working and socialising together for the benefit of everyone. What makes today’s coliving movement unique is the range of rapidly developing technology that is being implemented to improve the environments for tenants. As an arguably lower cost and higher quality way of life, coliving spaces are certainly here to stay, and so the PropTech surge is no doubt going to grow with it.

How AI is revolutionising fraud detection

The Annual Fraud Indicator estimates that fraud costs the United Kingdom approximately £190 billion every year. The private sector is hit the hardest and loses around £140 billion a year, while the public sector loses more than £40 billion, and individuals lose roughly £7 billion. The effects of fraud can be devastating on both individuals and organisations. Companies can suffer irreversible damage to reputation and be forced to close, and individuals can experience significant personal losses. Everyone should be aware of the risks and take steps to protect themselves against fraudulent activity. Fraud detection technology Fraud detection technology has advanced rapidly, over the years and made it easier for security professionals to detect and prevent fraud. Here are some of the key ways that Artificial Intelligence (AI) is revolutionising fraud detection - with insight from Tessema Tesfachew, the Head of Product at Avora. An anomaly can be described as a behaviour that deviates from the expected An anomaly can be described as a behaviour that deviates from the expected. According to Tessema Tesfachew, “Autonomous monitoring and anomaly detection specifically, have made detecting fraudulent activity faster and more accurate. Machines can monitor data 24/7 as it comes in, build patterns of behaviour that take into account seasonality and shifting trends, and identify events that don’t fit the norm.” For example, banks can use AI software to gain an overview of a customer’s spending habits online. Having this level of insight allows an anomaly detection system to determine whether a transaction is normal or not. Suspicious transactions can be flagged for further investigation and verified by the customer. If the transaction is not fraudulent, then the information can be put into the anomaly detection system to learn more about the customer’s spending behaviour online. Accurate root cause analysis Root cause analysis goes one step further than anomaly detection, by allowing security professionals to pinpoint what caused the anomaly. Tessema explains how an example of this would be if a system detects that the rate of fraudulent transactions has increased. Root cause analysis would pinpoint the specific ATM or point of sale, where this increase is occurring. Swift action can then be taken to prevent fraudulent activity at that location in the future. Fewer false positives As mentioned, false positives can occur if a fraud detection system identifies behaviour that goes against the norm, for instance, if a customer makes a transaction in a new location. In many cases, customers are required to complete identity verification to prove that a transaction is not fraudulent. Digital customer identity verification can help brands build a strong and reputable image. That said, forcing users to complete identify certifications regularly can cause frustration and harm the customer experience. AI anomaly detection AI fraud detection systems can carry out accurate data analysis in milliseconds and identify complex patterns in data AI anomaly detection is far more accurate and results in fewer false positives. Increasing the accuracy of anomaly detection helps companies improve customer relationships and build a strong reputation. This will have a positive impact on brand image and sales revenue. AI fraud detection systems can carry out accurate data analysis in milliseconds and identify complex patterns in data. Machines are more efficient than even the most skilled fraud analysts and make fewer errors. This is why AI fraud detection software is the preferred option in larger organisations. Importance of fraud analysts However, fraud analysts still play an important role in fraud prevention. Using a combination of human intervention and AI is usually the most effective approach when it comes to fraud detection. According to pymnts.com, innovative organisations now use a variety of AI and supervised and unsupervised machine learning to identify and protect against fraud. AI systems can complete time-consuming and repetitive tasks, such as data collection and analysis. This means that fraud analysts can focus their time and attention on critical tasks that require human intervention, e.g. monitoring risk scores. AI can automate processes and enhance the quality of the fraud analysts’ work. Conclusion In to Tessema Tesfachew’s opinion, “Fraud detection has become vastly more efficient and effective with the introduction of Artificial Intelligence (AI). Previously, methods for detecting fraudulent activities were still data-rich, but relied more on human intervention and expert bias, and were thus, more time consuming and prone to error.” AI technology, particular anomaly detection, has streamlined fraud detection and created a more efficient, and accurate system for detecting and preventing fraud. Covid-19 has increased the number of online transactions, which creates more opportunities for fraudulent activity. However, it also allows businesses to gain more information on their customers and enhance the capabilities of AI security software. It is more important than ever for organisations to utilise AI technology in fraud detection strategies.

What new technologies and trends will shape video analytics?

The topic of video analytics has been talked and written about for decades, and yet is still one of the cutting-edge themes in the physical security industry. Some say yesterday’s analytics systems tended to overpromise and underdeliver, and there are still some skeptics. However, newer technologies such as artificial intelligence (AI) are reinvigorating the sector and enabling it to finally live up to its promise. We asked this week’s Expert Panel Roundtable: What new technologies and trends will shape video analytics in 2021?