Ambarella, Inc., an AI vision silicon company, Lumentum, a designer and manufacturer of innovative optical and photonic products, and ON Semiconductor, a provider of CMOS image sensor solutions, announced a joint 3D sensing platform for the development of intelligent access control systems and smart video security products, such as smart video doorbells and door locks.
The platform is based on Ambarella’s CV25 CVflow AI vision system on chip (SoC), structured-light powered by Lumentum’s VCSEL technology, and ON Semiconductor’s AR0237IR image sensor. Ambarella, Lumentum, and ON Semiconductor will demonstrate the platform during CES 2020.
Lumentum has worked to enable diverse applications of our VCSEL technology into ext-generation 3D sensing products"
Traditional structured-light solutions need to use both an infrared (IR) camera and a separate RGB camera and typically, a dedicated ASIC for depth processing. This new platform leverages a single ON Semiconductor AR0237 RGB-IR CMOS image sensor to obtain both a visible image for viewing and an infrared image for depth sensing. The Ambarella CV25 AI vision SoC powers depth processing, anti-spoofing algorithms, 3D facial recognition algorithms, and video encoding on a single chip, significantly reducing system complexity while improving performance.
“Lumentum has worked to enable diverse applications of our VCSEL technology into next-generation 3D sensing products,” said Dr. Andre Wong, vice president, product line management, 3D Sensing at Lumentum. “We are excited to partner with Ambarella to help expand the use of 3D sensing in new applications including video security and more broadly AI vision.”
Single sensor solutions
“ON Semiconductor’s RGB-IR sensor technology enables single sensor solutions to provide both visible and IR images in security and vision IoT applications,” said Gianluca Colli, vice president and general manager of the Commercial Sensing Division at ON Semiconductor. “Ambarella’s CV25 computer vision SoC, with its next-generation image signal processor (ISP), brings out the best image quality of our RGB-IR sensor, while providing powerful AI processing capability for innovative use cases in security applications.”
It delivers 3D sensing with reduced system complexity as well as improved reliability and security
“We are delighted to partner with Lumentum and ON Semiconductor to deliver a hardware platform for the next generation of intelligent access control systems and video security devices,” said Fermi Wang, president and CEO of Ambarella. “Powered by Lumentum’s VCSEL solution, ON Semiconductor’s RGB-IR technology, and our CV25 SoC, it delivers 3D sensing with reduced system complexity as well as improved reliability and security. We look forward to seeing the innovative products our customers will build with this hardware platform.”
High dynamic range (HDR) processing
Ambarella’s CV25 chip includes a powerful ISP, native support for RGB-IR color filter arrays, and advanced high dynamic range (HDR) processing, which results in exceptional image quality in low-light and high-contrast environments. CV25’s CVflow architecture delivers the computational power required for liveness detection and 3D face recognition, while running multiple AI algorithms for advanced features such as people counting and anti-tailgating. CV25 includes a suite of advanced security features to protect against hacking including secure boot, TrustZone and I/O virtualisation.
The 3D sensing platform will be shown to select Ambarella and Lumentum customers and partners at their respective private events during CES 2020. ON Semiconductor will offer CES 2020 demonstrations of the 3D sensing platform in their demo room at the Venetian/Sands Convention center, Murano 3302.
Ambarella, Inc., an artificial intelligence (AI) vision silicon company, announced that Ambarella and Amazon Web Services, Inc. (AWS) customers can now use Amazon SageMaker Neo to train machine learning (ML) models once and run them on any device equipped with an Ambarella CVflow-powered AI vision system on chip (SoC). Until now, developers had to manually optimize ML models for devices based on Ambarella AI vision SoCs.
This step could add considerable delays and errors to the application development process. Ambarella and AWS collaborated to simplify the process by integrating the Ambarella toolchain with the Amazon SageMaker Neo cloud service. Now, developers can simply bring their trained models to Amazon SageMaker Neo and automatically optimize the model for Ambarella CVflow-powered SoCs.
Neural network accelerator
Customers can download the compiled model and deploy it to their fleet of Ambarella-equipped devices
Customers can build an ML model using MXNet, TensorFlow, PyTorch, or XGBoost and train the model using Amazon SageMaker in the cloud or on their local machine. Then, they can upload the model to their AWS account and use Amazon SageMaker Neo to optimize the model for Ambarella SoCs. They can choose CV25, CV22, or CV2 as the compilation target.
Amazon SageMaker Neo compiles the trained model into an executable that is optimized for Ambarella’s CVflow neural network accelerator. The compiler applies a series of optimization that can make the model run up to 2x faster on the Ambarella SoC. Customers can download the compiled model and deploy it to their fleet of Ambarella-equipped devices.
Enterprise video security
The optimized model runs in the Amazon SageMaker Neo runtime purpose-built for Ambarella SoCs and available for the Ambarella SDK.The Amazon SageMaker Neo runtime occupies less than 10x the disk and memory footprint of TensorFlow, MXNet, or PyTorch, making it much more efficient to deploy ML models on connected cameras.
“Ambarella is in mass production today with CVflow AI vision processors for the home monitoring, enterprise video security, and automotive markets,” said Chris Day, vice president of marketing and business development for Ambarella. "The ability to select an Ambarella SoC and compile a trained ML model with a single click is a powerful tool that makes it possible for our customers to rapidly bring the next generation of AI-enabled products to market.”
Advanced security features
AWS has the deepest set of ML and AI services focused on solving some of the toughest challenges facing developers"
Manufactured using an advanced 10-nanometer process, Ambarella’s CVflow SoC family enables the design of compact, high-performance vision systems with ultra-low power operation. For example, the Ambarella CV22 CVflow SoC delivers computer vision processing at full 4K or 8-megapixel resolution at 30 frames per second (fps), while its image signal processor (ISP) provides outstanding imaging in low- light conditions and high-contrast scenes, further enhancing the computer vision capabilities of the chip.
The CV22 also includes a suite of advanced security features to protect against hacking including secure boot, TrustZone, I/O virtualization, and support for online upgrades over the air (OTA).
Machine learning models
“AWS has the broadest and deepest set of ML and AI services focused on solving some of the toughest challenges facing developers. Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly,” said Bratin Saha, Vice President, Machine Learning & Engines, Amazon Web Services, Inc.
“We’re excited that VIVOTEK is using SageMaker Neo to simplify the deployment of ML models at the edge on Ambarella CVflow-powered IP cameras.”
Ambarella, Inc., an AI vision silicon company, announced the CV22FS and CV2FS automotive camera system on chips (SoCs) with CVflow AI processing and ASIL B compliance to enable safety-critical applications. Both chips target forward-facing monocular and stereovision ADAS cameras, as well as computer vision ECUs for L2+ and higher levels of autonomy.
Featuring extremely low power consumption, the CV22FS and CV2FS make it possible for tier-1s and OEMs to surpass New Car Assessment Program (NCAP) performance requirements within the power consumption constraints of single-box, windshield-mounted forward ADAS cameras. Other potential applications for the processors include electronic mirrors with blind spot detection (BSD), interior driver and cabin monitoring cameras, and around view monitors (AVM) with parking assist.
Intelligent viewing platforms
ZF is pleased to be working with Ambarella on the intelligent viewing platforms for Surround View Visualization"
The two new SoCs are the latest additions to Ambarella’s successful CVflow SoC family that offers automotive OEMs, tier-1s, and software development partners an open platform for differentiated, high-performance automotive systems. ZF, a global technology tier-1 and supplier of systems for passenger cars and commercial vehicles, is working with Ambarella on viewing and sensing systems:
“ZF is pleased to be working with Ambarella on the next generation of intelligent viewing platforms for Surround View Visualization, Driver Monitoring stand-alone vision processing, and e-mirror solutions for both the passcar and commercial vehicle markets,” said Aaron Jefferson, vice president of ADAS product planning at ZF. “The CVflow SoCs’ combination of high quality imaging and advanced AI processing enables ZF to offer a wide range of viewing and interior sensing applications.”
visual perception software
HELLA Aglaia, a global developer of intelligent visual perception software, has worked with Ambarella’s CVflow processors over the past year: “We chose Ambarella’s CVflow SoCs due to their ability to deliver extremely high computer vision processing performance with very low power consumption,” said Kay Talmi, managing director at HELLA Aglaia. “With the introduction of the CV22FS and CV2FS ASIL SoCs, Ambarella now delivers the functional safety features required by automotive OEMs for the mass production of safety-critical systems.”
“Ambarella’s CVFlow architecture delivers an unparalleled combination of AI performance and power efficiency,” said Fermi Wang, president and CEO of Ambarella. “We are pleased to introduce these ASIL compliant CVflow SoCs, delivering on our promises to our partners and customers and further demonstrating our commitment to the automotive market.”
Advanced stereovision applications
Ambarella will also demonstrate a range of applications from other key partners running on the CVflow engine
The CV22FS and CV2FS’s CVflow architecture provides computer vision processing in 8-megapixel or higher resolution at 30 frames per second for object recognition over long distances and with high accuracy. The SoCs each include a dense optical flow accelerator for simultaneous localisation and mapping (SLAM), as well as distance and depth estimation. Multi-channel high-speed sensor input and Ambarella’s image signal processing (ISP) pipeline provide the necessary camera input support, even in challenging lighting conditions. CV2FS also enables advanced stereovision applications by adding a dense disparity engine.
Ambarella will demonstrate its CVflow SoC family during CES 2020 to select customers and partners. Demonstrations will include HELLA Aglaia’s deep learning ADAS algorithms and Ambarella’s EVA (Embedded Vehicle Autonomy) self-driving prototype vehicle. Ambarella will also demonstrate a range of applications from other key partners running on the CVflow engine. CV22FS and CV2FS are scheduled to sample to Ambarella customers in the first half of 2020.
Wireless video streaming
CV22FS and CV2FS SoC key features:
CVflow architecture with DNN support
Quad-core 1-GHz Arm Cortex-A53 with NEON DSP extensions and FPU
Safety island with dual-core lock step (DCLS) Arm R52 targeting ASIL-C
Dense optical flow engine
Dense stereo disparity engine (CV2FS only)
ASIL B functional safety level - High speed SLVS/MIPI CSI-2/LVCMOS interfaces
Multi-channel ISP with up to 480-Megapixel/s input pixel rate
Native support for RGGB, RCCB, RCCC, RGB-IR, and monochrome sensor formats
Multi-exposure high dynamic range (HDR) processing and LED flicker mitigation
Real-time hardware-accelerated fish-eye dewarping and lens distortion correction (LDC)
4-megapixel AVC encoding for video logging and wireless video streaming
Rich set of interfaces includes CAN FD, Gigabit Ethernet, USB 2.0 host and device, dual SD card controllers with SDXC support, MIPI DSI/CSI-2 4-lane output
Advanced security features, including OTP for secure boot, TrustZone, and IO virtualization
AEC-Q100 grade 2 (-40C to +125C (TJ) operating temperature)
10 nm process technology
Ambarella, Inc., an AI vision silicon company, Lumentum, a designer and manufacturer of innovative optical and photonic products, and ON Semiconductor, a provider of CMOS image sensor solutions, announces a joint 3D sensing platform for the development of intelligent access control systems and smart video security products such as smart video doorbells and door locks.
The platform is based on Ambarella’s CV25 CVflow® AI vision system on chip (SoC), structured-light powered by Lumentum’s VCSEL technology, and ON Semiconductor’s AR0237IR image sensor. Ambarella, Lumentum, and ON Semiconductor will demonstrate the platform during CES 2020.
Significantly reducing system complexity
Lumentum has worked to enable diverse applications of our VCSEL technology into next-generation 3D sensing products"
Traditional structured-light solutions need to use both an infrared (IR) camera and a separate RGB camera and typically, a dedicated ASIC for depth processing. This new platform leverages a single ON Semiconductor AR0237 RGB-IR CMOS image sensor to obtain both a visible image for viewing and an infrared image for depth sensing.
The Ambarella CV25 AI vision SoC powers depth processing, antispoofing algorithms, 3D facial recognition algorithms, and video encoding on a single chip, significantly reducing system complexity while improving performance. “Lumentum has worked to enable diverse applications of our VCSEL technology into next-generation 3D sensing products,” said Dr. Andre Wong, vice president, product line management, 3D Sensing at Lumentum. “We are excited to partner with Ambarella to help expand the use of 3D sensing in new applications including video security and more broadly AI vision.”
Providing powerful AI processing capability
We are delighted to partner with Lumentum and ON Semiconductor to deliver a hardware platform"
“ON Semiconductor’s RGB-IR sensor technology enables single sensor solutions to provide both visible and IR images in security and vision IoT applications,” said Gianluca Colli, vice president and general manager of the Commercial Sensing Division at ON Semiconductor. “Ambarella’s CV25 computer vision SoC, with its next-generation image signal processor (ISP), brings out the best image quality of our RGBIR sensor, while providing powerful AI processing capability for innovative use cases in security applications.”
“We are delighted to partner with Lumentum and ON Semiconductor to deliver a hardware platform for the next generation of intelligent access control systems and video security devices,” said Fermi Wang, president and CEO of Ambarella.
Improved reliability and security
“Powered by Lumentum’s VCSEL solution, ON Semiconductor’s RGB-IR technology, and our CV25 SoC, it delivers 3D sensing with reduced system complexity as well as improved reliability and security. We look forward to seeing the innovative products our customers will build with this hardware platform.”
Ambarella’s CV25 chip includes a powerful ISP, native support for RGB-IR color filter arrays, and advanced high dynamic range (HDR) processing, which results in exceptional image quality in low-light and high-contrast environments. CV25’s CVflow architecture delivers the computational power required for liveness detection and 3D face recognition, while running multiple AI algorithms for advanced features such as people counting and anti-tailgating. CV25 includes a suite of advanced security features to protect against hacking including secure boot, TrustZone®, and I/O virtualization.
On November 2019 in Stockton, California, surveillance footage found that vandals shot out glass windows and doors in many places in a small business complex (FOX40). The intruders broke in only to leave with nothing, proving their intent was solely to vandalize the property. Meanwhile, it was reported that a trio of ATM thieves struck around 9 times across many different locations inside Brooklyn and Queens within just over a month in fall 2019 (ATM Marketplace).
On average, the cost of vandalism to SMB is around $3,370 per incident (US Small Business Administration), including a staggering 692 vehicle vandalism claims per day. Likewise, the average cost of theft to SMB is about $300 per shoplifting incident and $1,500 per employee theft incident, which accounts for 38% and 34.5% of all theft instances, respectively (National Retail Security Survey).
High-performance artificial intelligent systems can automate the monitoring tasks
Vandalism and theft have proven time and time again to be inconvenient and deconstructively harmful towards SMB. However, these financial burdens can be prevented with the use of the right security system. AI-based security systems with Deep Learning contain many features that many SMB owners find advantageous in their pursuit to stop unwarranted and unwanted money loss.
Intrusion and loitering detection
The first of many features that can help with vandalism and theft prevention is Intrusion Detection. High-performance artificial intelligent systems can automate the monitoring tasks for high-risk sites to provide a high level of security and security personnel monitoring efficiency. Traditional intrusion detection systems detect objects based on size and location, but they do not recognize the type of objects.
Now, Intrusion Detection (Perimeter Protection) systems with cutting-edge, built-in AI algorithms to recognize a plethora of different object types, can distinguish objects of interest, thus significantly decreases the false-positive intrusion rate. The more advanced AI-based systems, like those we offered at IronYun, enable the users to draw ROIs based on break-in points, areas of high-valuables, and any other preference to where alerts may be beneficial.
Similarly, AI Loitering Detection can be used to receive alerts on suspicious activity outside any given store. The loitering time and region of interest are customizable in particular systems, which allows for a range of detection options. Advanced loitering detection software as such can detect and trigger real-time alerts for both people loitering and/or vehicles that are illegally parked in certain areas of interest. A benefit, which only certain advanced systems contain, is the ability to send trigger actions to 3rd-party systems in reaction to receiving an alert of loitering and/or intrusion detection. These trigger actions can be set to contact authorities immediately and/or trigger a scare tactic alarm or announcement to intruder/loiterer.
Certain Face Recognition and License Plate Recognition software can record individual people/vehicles
Face and license plate recognition
In addition to the activity detection solutions, certain Face Recognition and License Plate Recognition software can record individual people/vehicles and use pre-configured lists to identify particular faces or plates that may be of interest, such as those in watchlists. These systems can also enable the users to upload images of faces not in the lists and search for them in the camera recording. For instance, if a person is detected several times loitering outside a store, one may save one of the detection photos into the watchlist, and set up an alert when said face is recognized again outside the building in the future. The alerts will help to deter and prevent vandalism or theft, and notify the authorities to the scene before the troublemaker completes the act. The main attributes of high-performance Face Recognition systems which maximize assistance with vandalism and theft management include:
Face match rate > 90% with good camera angles and lighting.
Processing multiple streams and multiple faces per image.
Live face extraction and matching to databases of thousands of faces within 3 seconds.
State-of-the-art AI security software with Deep Learning allows the user to no longer need to install special LPR cameras
If the watchlist individual is wearing a mask or their face is not in view of the camera, their license plate may be a good indicator. If a particular car is detected several times loitering in the parking lot or street outside a store, the user can set the alerts for such car to get notified in the future. With an AI solution like this, common street cameras should be equipped with LPR capabilities. So, state-of-the-art AI security software with Deep Learning allows the user to no longer need to install special LPR cameras.
high-performance alert mechanisms
A high-performance AI solution, in addition to having high accuracy, should be able to:
Easily integrate with 3rd-party systems
Work well with all ONVIF IP cameras including infrared and thermal ones (for Intrusion detection)
Analyzes video streams in real time and trigger alerts within a few seconds
Send alerts to multiple VMSs, connect with signaling devices such as loud speakers or flashing lights
Send email notifications to security staff and police departments
Send notification on mobile device using AI NVR mobile app
Maintains a record of all alerts to provide evidence of intrusion and loitering instances for police and insurance agencies.
To assist in theft and vandalism prevention, AI-based security systems with deep learning will do all of the tedious work for you. Their low cost and high performance also make them the most accessible security solutions in the market with large return on investment. Stopping crimes is a difficult, ongoing challenge, but with the right AI software, business vendors and police departments can do so with more ease.
As we surpass 2019, it’s high time we realize that by merging the digital and physical realm, IoT is destined to change the way we live and work.
I have always been interested in the intersection between business and technology, and today it seems that the brave new technological world we have been dreaming over centuries has arrived. With everything from home appliances to smart vehicles, portable devices are connected to the internet and exchange crucial data. According to the statistics, there are 26.66 billion IoT connected devices around the globe. Which statistically leaves every citizen of the world with at least 3 devices.
IoT in every day life
I must say the numbers are quite mind-boggling! And this leaves a lot of room for improvement by incorporating the Internet of Things in software development; whether it’s a cellphone app or web.
According to the statistics, there are 26.66 billion IoT connected devices around the globe. Which statistically leaves every citizen of the world with at least 3 devices It may interest you to know that the Internet of Things has the potential to touch every domain and nearly every aspect of human life. According to sources, impact on IoT leads to:
By 2020, 50 billion devices are expected to connect to the internet
In 2015, 3.5 connected devices per person have now reached almost 7
8 billion cellphone broadband access points by 2019
5 million IoT jobs by 2020
70 percent a year growth through 2018 in total sales of clothing and accessories incorporating computer technology, rising from $3 billion today to $42.5 billion
$3.3 trillion market for ‘Smart City’ applications and services by 2025
The impact of smart homes
Instead of saying the home is where our heart is; a home is where a bot is. However, IoT hasn’t entirely arrived in our homes. I mean, we are still required to order groceries the minute we run out of eggs and Greek yogurt. Slowly and steadily we are getting there; it seems the latest advancements in artificial intelligence and big data analytics will definitely work wonders for us.
Smart homes are no longer a dream project; we can soon expect everything to be governed by the “brain” or a central platform. Moreover, bots will be seen tackling a certain set of functions related to more difficult tasks, and lastly niche bots, in charge of single tasks such as vacuuming the house or addressing more complex duties like accounting, coaching or household managing. Tech giants, or should I call them current development frontrunners like Amazon, Google, Samsung and Apple are expected to come up with something nerve-cracking.
The benefits of IoT
Other than this, with IoT, you will be able to work smarter and not harder. Artificial intelligence and advanced analytics can help create a more intelligent work environment. For example, the right AC temperature in shared office spaces help us book the most convenient meeting room, and moreover, take into account the room preference by setting the right temperature, lighting, and can automatically restock office supplies.
This simply leads to:
More efficient office operations
Comfortable work environments
Consequently increased employee productivity
The dark side of the Internet of Things
The potential risks
Every technology indeed comes as a boom, but that doesn’t mean the grass will be greener on the other side. Furthermore, we will uncover how even after offering so much convenience why IoT poses so much risk. Like I said before, IoT can be integrated into anything from coffee machines to fitness watches leading to make our lives more convenient. But what happens if they turn bad? When being unwillingly infected or hacked, these blessings can certainly turn into huge threats.
IoT can be integrated into anything, leading to make our lives more convenient
Devices, systems and the lack of security
It may interest you to know that IoT devices can become bots that blindly follow commands to commit crimes as part of a botnet. What is a botnet, you may ask? Well, it is a network of infected devices that are mainly abused by the attacker to perform tasks such as carrying out DDoS attacks, Bitcoin mining and spreading spam emails. Mainly being used to carry out DDoS attacks and to mine for cryptocurrencies, these botnets have the potential to have a larger impact by making IoT devices do much more, such as send spam messages featuring dangerous malware. Botnets can also carry out click-jacking campaigns, distribute fake advertisements, and even worse, infect other IoT devices.
Botnets can also carry out click-jacking campaigns, distribute fake advertisements, and even worse, infect other IoT devices Much like most malware, botnets can be found on dark marketplaces. The source code can be purchased and leaked, depending on the type of service. In case, an IoT device is already infected, another bot can attempt to replace the infection with its code and in some cases also "repair" the security vulnerability. But most of the time it fails! No matter how innocent these proof-of-concept attacks may seem, one cannot deny the fact that IoT devices and systems aren’t properly secured. Hackers can easily gain control of them and cause complete chaos like never before.
Collecting information at a cost
But how much information can an IoT device collect? What I mean is that by hacking a webcam, one can see what they are pointed at without you even knowing it, smart TVs and personal assistants can pick up sound, and smart cars can give clues to whether or not someone is home. Honestly, the amount of information collected on these IoT devices cannot be determined at any cost. And with everything in the cloud, such information can be intercepted or rerouted to a malicious server and be abused if not properly secured.
The more we surround ourselves with IoT devices, the more motivation cybercriminals receive to target us! With the time passing by, let’s simply hope that connected device security will dramatically improve.
Imagine a home surveillance camera monitoring an elderly parent and anticipating potential concerns while respecting their privacy. Imagine another camera predicting a home burglary based on suspicious behaviors, allowing time to notify the homeowner who can in turn notify the police before the event occurs—or an entire network of cameras working together to keep an eye on neighborhood safety.
Artificial Intelligence vision chips
A new gen of AI vision chips are pushing advanced capabilities such as behavior analysis and higher-level security
There's a new generation of artificial intelligence (AI) vision chips that are pushing advanced capabilities such as behavior analysis and higher-level security to the edge (directly on devices) for a customizable user experience—one that rivals the abilities of the consumer electronics devices we use every day.
Once considered nothing more than “the eyes” of a security system, home monitoring cameras of 2020 will leverage AI-vision processors for high-performance computer vision at low power consumption and affordable cost—at the edge—for greater privacy and ease of use as well as to enable behavior analysis for predictive and preemptive monitoring.
Advanced home monitoring cameras
With this shift, camera makers and home monitoring service providers alike will be able to develop new edge-based use cases for home monitoring and enable consumers to customize devices to meet their individual needs. The result will be increased user engagement with home monitoring devices—mirroring that of cellphones and smart watches and creating an overlap between the home monitoring and consumer electronics markets.
A quick step back reminds us that accomplishing these goals would have been cost prohibitive just a couple of years ago. Face recognition, behavior analysis, intelligent analytics, and decision-making at this level were extremely expensive to perform in the cloud. Additionally, the lag time associated with sending data to faraway servers for decoding and then processing made it impossible to achieve real-time results.
Cloud-based home security devices
The constraints of cloud processing certainly have not held the industry back, however. Home monitoring, a market just seven years young, has become a ubiquitous category of home security and home monitoring devices. Consumers can choose to install a single camera or doorbell that sends alerts to their phone, a family of devices and a monthly manufacturer’s plan, or a high-end professional monitoring solution.
While the majority of these devices do indeed rely on the cloud for processing, camera makers have been pushing for edge-based processing since around 2016. For them, the benefit has always been clear: the opportunity to perform intelligent analytics processing in real-time on the device. But until now, the balance between computer vision performance and power consumption was lacking and camera companies weren’t able to make the leap. So instead, they have focused on improving designs and the cloud-centric model has prevailed.
Hybrid security systems
Even with improvements, false alerts result in unnecessary notifications and video recording
Even with improvements, false alerts (like tree branches swaying in the wind or cats walking past a front door) result in unnecessary notifications and video recording— cameras remain active which, in the case of battery powered cameras, means using up valuable battery life.
Hybrid models do exist. Typically, they provide rudimentary motion detection on the camera itself and then send video to the cloud for decoding and analysis to suppress false alerts. Hybrids provide higher-level results for things like people and cars, but their approach comes at a cost for both the consumer and the manufacturer.
Advanced cloud analytics
Advanced cloud analytics are more expensive than newly possible edge-based alternatives, and consumers have to pay for subscriptions. In addition, because of processing delays and other issues, things like rain or lighting changes (or even bugs on the camera) can still trigger unnecessary alerts.
And the more alerts a user receives, the more they tend to ignore them—there are simply too many. In fact, it is estimated that users only pay attention to 5% of their notifications. This means that when a package is stolen or a car is burglarized, users often miss the real-time notification—only to find out about the incident after the fact. All of this will soon change with AI-based behavior analysis, predictive security, and real-time meaningful alerts.
Predictive monitoring while safeguarding user privacy
These days, consumers are putting more emphasis on privacy and have legitimate concerns about being recorded while in their homes. Soon, with AI advancements at the chip level, families will be able to select user apps that provide monitoring without the need to stream video to a company server, or they’ll have access to apps that record activity but obscure faces.
Devices will have the ability to only send alerts according to specific criteria. If, for example, an elderly parent being monitored seems particularly unsteady one day or seems especially inactive, an application could alert the responsible family member and suggest that they check in. By analyzing the elderly parent’s behavior, the application could also predict a potential fall and trigger an audio alert for the person and also the family.
AI-based behavior analysis
Ability to analyze massive amounts of data locally and identify trends is a key advantage of AI at the edge
The ability to analyze massive amounts of data locally and identify trends or perform searches is a key advantage of AI at the edge, for both individuals and neighborhoods. For example, an individual might be curious as to what animal is wreaking havoc in their backyard every night.
In this case, they could download a “small animal detector” app to their camera which would trigger an alert when a critter enters their yard. The animal could be scared off via an alarm and—armed with video proof—animal control would have useful data for setting a trap.
A newly emerging category of “neighborhood watch” applications is already connecting neighbors for significantly improved monitoring and safety. As edge cameras become more commonplace, this category will become increasingly effective.
The idea is that if, for example, one neighbor captures a package thief, and then the entire network of neighbors will receive a notification and a synopsis video showing the theft. Or if, say, there is a rash of car break-ins and one neighbor captures video of a red sedan casing their home around the time of a recent incident, an AI vision-based camera could be queried for helpful information:
Residential monitoring and security
The camera could be asked for a summary of the dates and times that it has recorded that particular red car. A case could be made if incident times match those of the vehicle’s recent appearances in the neighborhood. Even better, if that particular red car was to reappear and seems (by AI behavior analysis) to be suspicious, alerts could be sent proactively to networked residents and police could be notified immediately.
Home monitoring in 2020 will bring positive change for users when it comes to monitoring and security, but it will also bring some fun. Consumers will, for example, be able to download apps that do things like monitor pet activity. They might query their device for a summary of their pet’s “unusual activity” and then use those clips to create cute, shareable videos. Who doesn’t love a video of a dog dragging a toilet paper roll around the house?
AI at the Edge for home access control
Home access control via biometrics is one of many new edge-based use cases that will bring convenience to home monitoring
Home access control via biometrics is one of many new edge-based use cases that will bring convenience to home monitoring, and it’s an application that is expected to take off soon. With smart biometrics, cameras will be able to recognize residents and then unlock their smart front door locks automatically if desired, eliminating the need for keys.
And if, for example, an unauthorized person tries to trick the system by presenting a photograph of a registered family member’s face, the camera could use “3D liveness detection” to spot the fake and deny access. With these and other advances, professional monitoring service providers will have the opportunity to bring a new generation of access control panels to market.
Leveraging computer vision and deep neural networks
Ultimately, what camera makers strive for is customer engagement and customer loyalty. These new use cases—thanks to AI at the edge—will make home monitoring devices more useful and more engaging to consumers. Leveraging computer vision and deep neural networks, new cameras will be able to filter out and block false alerts, predict incidents, and send real-time notifications only when there is something that the consumer is truly interested in seeing.
AI and computer vision at the edge will enable a new generation of cameras that provide not only a higher level of security but that will fundamentally change the way consumers rely on and interact with their home monitoring devices.
Security’s intersection with consumer electronics is on view at CES 2020, the world’s largest technology event, Jan. 7-10 in Las Vegas. The giant show features more than 170,000 attendees, 4,500 exhibitors and 1,100 industry thought-leaders featured on the CES stage.
A range of technologies will be on display, from artificial intelligence (AI) to 5G, vehicle technology to AR/VR (augmented and virtual reality), robotics to home automation. Security plays a prominent role, too.The impact of this event for the smart home could be about delivering home analytics and enhancing privacy"
Smart home market on the forefront
The smart home market is a major focus. “For the smart home market at CES this year, we expect to see numerous announcements regarding home awareness,” says Blake Kozak, Senior Principal Analyst at IHS Markit. “This will include brands offering up additional analytics for consumer security cameras with a focus on edge-based solutions.”
“The impact of this [event] for the smart home could be about delivering home analytics and enhancing privacy through cloudless architectures and new electronic door lock approaches,” he adds. An example of cloud analytics is the Resideo Home app, introduced in December, which will make whole-home monitoring possible for four critical networks of the home – water, air, energy and security. Resideo promises a “simplified and integrated smart home experience.”
Video is also prominent at the show. “For cameras, we can expect to see more cameras focused on the outdoor space and possibly new form factors for video doorbells,” says Kozak. Familiar security industry brands exhibiting at CES 2020 include ADT, Ring, August Home and Yale (both part of ASSA ABLOY), Bosch and Alarm.com.
Focus on Cybersecurity
In 2020, companies will continue to focus on solutions for protecting consumer data"
Cybersecurity is an aspect of many of the devices on display at CES. “Device security and data privacy play a key role in the adoption of connected devices,” says Elizabeth Parks, President, Parks Associates.
“Consumer security concerns for smart home products will continue to be a barrier to adoption in the U.S. and Europe, and these concerns can actually intensify with device adoption-71% of U.S. smart home households are concerned about cybersecurity. In 2020, companies will continue to focus on solutions for protecting consumer data. One big area of interest is protection on the network router, providing whole home solutions, which are very appealing to consumers.”
“At CES we will see the traditional players introducing new DIY (do-it-yourself) products, as well as new players announcing new product features, services, and partnerships,” Parks adds.
Smart access control
Smart locks will be among the security products at CES 2020. For example, PassiveBolt, a lock company, will show the Shepherd Lock, a touch-enabled smart lock with enhanced security through sensors and AI. The add-on lock converts existing locksets into touch-activated devices. Another lock manufacturer is Kwikset, whose door locks and door hardware include Wi-Fi-enabled smart locks, Bluetooth-enabled smart locks, keyless and keyway-less locks and connected home technology.
Video doorbells, including industry-innovator Ring, have been a hit in the consumer market. At CES, Ring will expand the mission to make neighborhoods safer by creating a “Ring of Security” around homes and communities with a suite of home security products and services. The “Neighbors by Ring” app enables affordable, complete, proactive home and neighborhood security.
Homeguard offers a range of affordable CCTV solutions for home and small business
DIY CCTV demonstrations
DIY security systems are another market. Homeguard is a leading DIY consumer brand offering a range of affordable CCTV solutions for home and small business, including wired and wireless CCTV kits, smart cameras, home alarm systems and wire-free HD CCTV kits.
Swann Communications is also at the forefront of surveillance and monitoring with new products developments including wire-free HD cameras and doorbells, professional CCTV video surveillance systems, and 1080p full HD systems with “True Detect” heat and motion sensing.
AVTECH, and subsidiary YesGo Tech, will demonstrate a compact Wi-Fi home security set, a series of special cameras with face recognition, thermal detection and license plate recognition, customized central management software and a university ID tag that is compatible with access control, OEM and ODM opportunities.
Security and automation solutions
D-Link’s home networking, security and automation solutions will help consumers connect, view, share, entertain, work and play. SECO-LARM, manufacturer of a Room Occupancy Monitor that shows whether a room is in use, has a line of keypads and proximity readers with built-in Bluetooth for convenient access.
Another smart home security solutions provider, Climax Technology, integrates wireless security, home automation, energy management, home emergency monitoring and live visual monitoring.
Personal safety mobile application
Manufacturers are positioning outdoor cameras as deterrents to theft before a burglary happens"
WaryMe designs and develops a personal safety mobile application to improve a user’s security in public places, schools, transports and companies by addressing major risks such as terrorism attacks, intrusion, fire and even industrial accidents. An all-in-one mobile application integrates alerting, crisis management and mass notification features.
“Market players are looking to expand beyond established smart home devices like smart thermostats and networked cameras to products like smart water leak detectors, smart pet feeders, and smart air purifiers,” says Elizabeth Parks. “Manufacturers are positioning outdoor cameras as deterrents to theft before a burglary happens. This trend is part of a broader security marketing effort to extend the perimeter of home security beyond traditional home access points.”
“Familiarity with smart home devices lags behind familiarity with smart entertainment products; it even lags that of smart speakers, which are quite new in the market,” adds Parks. “In 2020, we will see players working to advance the visibility and marketing around device integration, and specifically focus on use case scenarios around safety, security, and convenience, which have always been the primary drivers of adoption of these types of products.”
Technology is expanding passenger screening functions and other capabilities at airport security checkpoints. For example, Smiths Detection is exploring the concept of a security checkpoint that integrates biometric identity management with screening solutions, says Richard Thompson, Global Market Director Aviation, Smiths Detection.
Biometrics is the “unique identifier’” for passengers, and through integration of biometrics directly into the checkpoint, passengers can be matched with their luggage trays to enable real-time risk-based screening (RBS). The system is now able to trigger differentiated workflows for each passenger and their bags.
Risk-based screening optimizes security operator resources through enhanced screening of passengers who represent a higher risk, while passengers deemed to be low risk enjoy a more seamless journey.Passengers deemed to be low risk enjoy a more seamless journey
Easily integrated with existing infrastructure, biometric checkpoints deliver operational efficiencies and a competitive advantage to airports through accelerating the screening process, thus enabling a more seamless free flow of passengers.
Passenger and tray identification
Through passenger and tray identification, new data insights can also be gathered to inform decision-making. Advanced data analysis based on flights, airlines or destinations could be utilized by airlines and security authorities.
For example, airlines could monitor passenger flow through security for specific flights or track the number of trays per flight to predict overhead compartment capacity. Checkpoint data could also be combined with hold luggage screening results or shared with transit and arrival airports to better inform security assessments.
Advanced data analysis based on flights, airlines or destinations could be utilized by airlines and security authorities
Advanced screening of carry-on baggage
Smiths Detection’s HI-SCAN 6040 CTiX offers advanced screening of carry-on baggage using Computed Tomography (CT), an advanced X-ray technology originally intended for medical applications, which allows for detailed, layered 3D images to be rotated and dissected. Electronic devices and liquids do not need to be removed from baggageThis enables detailed detection, meaning electronic devices and liquids do not need to be removed from baggage, thus expediting screening and further improving the passenger journey.
Smith Detection’s iLane.evo is an automatic tray return system. By delivering a steady flow of trays, it plays a critical role in streamlining the screening process and delivering increased throughput; optimized operational costs; and an improved passenger experience.
AI for Object Recognition
In other trends, the use of artificial intelligence (AI) in aviation security is on the rise due to the exponential growth in computing power. It has the potential to significantly boost the performance of screening equipment – allowing for the deployment of new object recognition functions at the checkpoint, which could pave the way for a more automated, alarm-resolution-only passenger screening. Smiths Detection has developed a family of smart algorithms, called iCMORE, which use machine learning to reliably detect prohibited or dangerous goods in baggage, including weapons, to reduce the burden on image analysts and improve screening outcomes.
As security embraces IT-centric solutions, it can provide business value over and above security. Now in charge of managing a variety of data – e.g., from video platforms – a company’s security function has access to a range of new metrics.
While security may use video to analyze a security event, machine learning can analyze the same data for other business capabilities, such as quality control or when a policy has been breached. “It’s the same camera, but with dual purpose,” says Matt Kushner, President of STANLEY Security.
STANLEY Security, one of the largest integrators with a global footprint, has positioned itself at the center of the industry’s transformation by information technology (IT) and the Internet of Things. “Security will become an expanded business partner with corporations,” Kushner comments. In response to the trend, STANLEY is hiring more IT-oriented technicians and salespeople within the IT community and who can “speak at the C-level,” Kushner comments.
Sonitrol is the most recognised brand by law enforcement for verified response
Data centers, higher education and logistics
STANLEY manages very large, multi-national clients. As a consequence, the STANLEY security organization has some of the best and brightest minds for enterprise-class security. To maintain that level of talent, STANLEY is committed to education. “We bring them into the family and focus on education, such as IT and IoT training. That’s critical in a world where unemployment is less than 3%. Finding good people, growing good people, and retaining good people – we do that exceptionally well at STANLEY,” says Kushner.
STANLEY’s strong vertical markets including data centers, higher education, and logistics. They are also strong in multi-location installations (such as banking.) STANLEY has a big footprint throughout North America and Europe.
PACOM access control and 3xLOGIC cloud-based solutions
In addition to STANLEY’s core integrator business, the company also manages several manufacturing brands such as PACOM access control and 3xLOGIC cloud-based solutions. Mergers and acquisitions have been commonplace in the integrator spaceBeyond its company-owned integrator locations under the STANLEY brand, the company also owns Sonitrol, the strongest brand in the market for verified response with 65 franchises in North America. Sonitrol is the most recognized brand by law enforcement for verified response.
Mergers and acquisitions have been commonplace in the integrator space, and Kushner says that STANLEY is “open and actively looking for properties that fit our commercial growth strategy.” He notes that STANLEY focuses on the commercial side of the market, where there are good margins and continuing growth. They pay less attention to the residential side which is “being heavily disrupted.”
Strong partnerships with manufacturers
STANLEY has strong partnerships with several manufacturer partners, through which they bring new breakout technologies to market from emerging companies. An example is Evolv Technology, a manufacturer of gun and bomb detection technology. “We see them as a leading provider of the technology, and they are, in my mind, a very disruptive provider,” says Kushner. STANLEY is also collaborating with a company – to be announced – that provides a unique gunshot detection technology, he says.
STANLEY is also cooperating with dormakaba to implement Switch Tech, a Bluetooth wireless core that can replace any standard mechanical lock core. Existing locks can be transformed into electromechanical locks in minutes. STANLEY is also developing a tight integration with Lenel’s mobile credentialing system.
STANLEY is also cooperating with dormakaba to implement Switch Tech
GSX 2019 and ISC West 2020
At the recent GSX 2019 show in Chicago, Kushner says STANLEY heard a lot about cybersecurity, especially customers wanting to make sure they are investing in cyber-hygiene and who are looking to expand into providing cyber protection. “In concert with cyber-hygiene, they are looking for health monitoring or assurance that network devices are operating properly,” he says. “They want to ensure their security platforms are cyber-secure and up to date with the latest software versions.”
STANLEY is also a big proponent of cloud offerings, and Kushner hints at a big announcement at the upcoming ISC West show in Las Vegas of additional cloud offerings and/or partnerships. “There will be a variety of new solutions to be introduced, including hosted solutions and applications that benefit both security and that add new value to businesses overall.”
Videonetics has supported Nagpur in achieving the Smart City status, under the Smart City Mission of Government of India, by securing its roads with an AI & DL powered Intelligent Traffic Management Solution. The solution has helped the city to solve its traffic enforcement problems such as red light jumping, crosswalk/ stop line violations, over speeding violations, tracking of suspect/ stolen vehicle, and generating e- challan/ e ticket for violators as per the Motor Vehicles Act. It includes applications like Automatic Number Plate Recognition (ANPR), Red Light Violation Detection (RLVD), Integrated eChallan Management Software.
With the successful implementation of the solution, Nagpur has witnessed greater traffic discipline and substantial decrease in traffic violations. More efficient traffic management has helped the city achieve its Smart City objectives.
Intelligent Traffic Management System
Nagpur has witnessed a rapid rise in the number of vehicles, and also in traffic violations and road accidents
Over the last few years, Nagpur has witnessed a rapid rise in the number of vehicles, and also in traffic violations and road accidents. The city administration recognized the need to enhance road safety, and the traffic police department sought a solution that would act as a true decision support system to regulate and analyze vehicle movement on roads. In addition, the police expected the solution to assist them in maintaining law and order, to identify frequent offenders as well as stolen/ suspect vehicles, as and when they enter the city.
With the city needing to enhance its road safety even as it was expanding, Videonetics designed a solution based on its Intelligent Traffic Management System that provides continuous monitoring of the traffic situation, records traffic violations at intersections, and triggers necessary penal action against violators.
Manage real-time alerts
24x7 real-time monitoring: Today, the city has ANPR and RLVD systems spread across 120 traffic junctions, to track and record license plate of any type of vehicle, as well as detect red light or stop line violation at intersections. Nearly 1,300 IP cameras have been deployed, to monitor vehicle movement and detect suspect vehicles simultaneously.
Violation prosecution: Videonetics’s Integrated e-Challan/e-Ticket Management Software has been assimilated with Regional Transport Office database, to fetch the details of a vehicle and its owner. Once a violation is detected, an e-challan is issued to the offender. The e-challan also maintains a record of all payments, both received and pending.
A centralized security view: The solution provides the police a bird’s eye view of the traffic junctions and city’s roads, from the Command & Contro Center. From the unified interface, security operators can view, manage real-time alerts and respond them swiftly.
City surveillance system
Prior to the installation of Videonetics’s Smart City solution, Nagpur city relied on on-site traffic monitors/ police to catch offending vehicles. However, the recent implementation of the solution has eliminated the need for physical deployment of traffic police at each junction. Videonetics’s solution helps maintain the security on city’s roads by detecting and recording traffic violations with accuracy, resulting in irrefutable evidence for local authorities.
In addition, citizens have started obeying traffic rules, resulting in an over 50% reduction in traffic violations. The open architecture of the solution not only allows the city to continue adding more applications to make its traffic management more robust, but also integrate with the city surveillance system in a single unified interface, to address security concerns with a holistic approach.
Haier Group, China’s home appliance manufacturer, has built a new industrial park in Russia to cope with the growing demand in Europe. Covering a total area of about 124.9 hectares, the new site is located in Naberezhnye Chelny, an important industrial city in Tatarstan, Russia.
With the gradual completion of its factories in the industrial park, Haier is looking for an intelligent system to realize multiple tasks within the whole industrial park. First, to prevent theft and timely detect people climbing over the perimeter fence. Second, to provide comprehensive monitoring in the whole industrial park and inside the factory which includes: monitoring of production line and employees’ smoking behavior during working hours at office areas; efficient employee attendance; vehicle identification at the entrance and exit areas of the industrial park; and the overall management of all devices, data report output, etc.
The Dahua Russia team designed a complete smart solution incorporating AI cameras, perimeter cameras, ANPR system, access control, time attendance system, face recognition barrier, DSS PRO platform and EVS storage for Haier’s industrial park. Notably, all of the devices were integrated in one central management platform, making it easier for operators to control and manage the system. In addition, the system also supports further device upgrade based on customer’s future plan for the next several years.
AI-powered perimeter protection function can greatly reduce false alarms caused by irrelevant objects
To help Haier solve the first problem, Dahua 5MP WDR IR Bullet AI Network Cameras were chosen to safeguard the perimeter of the Haier industrial park. Featuring active deterrence, the cameras are able to proactively warn intruders to leave before users take action. Once an intrusion is detected, a white light will turn on, accompanied by a buzzer to warn off the intruder. Additionally, its AI-powered perimeter protection function can greatly reduce false alarms caused by irrelevant objects. The combination of advanced AI analytics and real-time alerts to a desktop or mobile clients reduces system requirements and resources, thereby improving the efficiency of the surveillance system.
Smart IR technology
The office areas and the interior of the washing machine factory are covered with Dahua 4MP WDR IR Dome Network Cameras, while public areas are monitored by 2MP 25x Starlight IR PTZ Network Cameras.
As a member of Dahua Eco-savvy product family, the Dahua 4MP WDR IR Dome Network Cameras adopt upgraded H.265 encoding technology to provide starlight, Smart IR technology, as well as intelligent image analysis techniques. It saves bandwidth and storage, with energy-saving design to enhance monitoring performance of the system. With built-in Intelligent Video System (IVS) analytic algorithm, these dome cameras also support intelligent functions to monitor a scene for tripwire violations, intrusion detection, and abandoned or missing objects. In the future, it can respond quickly and accurately to events in the monitored areas.
These cameras are equipped with smooth control, high quality image and good protection
As for public areas, Dahua 2MP 25x Starlight IR PTZ Network Cameras have powerful optical zoom and accurate pan/tilt/zoom performance that can provide a large monitoring range and rich details. Through the latest Starlight technology, the cameras can achieve excellent low-light performance. In addition, these cameras are equipped with smooth control, high quality image and good protection, which meet the requirements of most industrial parks.
Dahua face recognition barriers were deployed at the entrance of the Haier industrial park and its office building, allowing quick and touchless passage of registered Haier employees without using employee cards or other identification documents. The system is based on a deep learning algorithm powered by AI, which compares facial images captured by the camera with those stored in the library to verify a person’s identity and grant permission. Access will be denied for unregistered people.
The industrial park’s entrance and exit use 2 Megapixel Full HD AI Access ANPR Cameras to identify entering and exiting vehicles. Boasting a capture rate of over 99%, the cameras can automatically recognize the number plate of a vehicle in low speed less than 40 kmph, and capture vehicle data such as vehicle direction, vehicle size and vehicle color detection (in daytime) based on deep learning algorithm. Aside from these capabilities, the cameras can also control the barrier according to the whitelist set by users and let registered vehicles pass without stopping.
The Dahua DSS PRO management platform integrates all cameras and the aforementioned devices
At the management center, all the information collected by font-end cameras will be transferred to a 16-HDD Enterprise Video Storage. With Seagate HDD, the device offers unparalleled capacity performance for users to store massive videos and obtain evidence when needed. The Dahua DSS PRO management platform integrates all cameras and the aforementioned devices, allowing operators to easily control and manage the system.
Up-to-date Dahua AI equipment
Dahua Technology’s smart industrial park solution has assisted Haier in creating a modern intelligent industrial park in Russia. The up-to-date Dahua AI equipment provides Haier a long-term smart security system with upgraded security level and enhanced management efficiency.
“The traditional personnel management system requires manual registering of employee information and cards to enter and exit office areas, which is inefficient and difficult to manage, and often high in cost. Upgrading the access verification system is crucial for modern companies like Haier in order to increase the security level of its industrial park and office building. We look forward to our future cooperation,” said Zhao Shengbo, Regional Director of Dahua CIS.
“During the requirement discussion, solution design, and engineering survey, Dahua shows professionalism and excellent communication skills. Haier is satisfied with the first step cooperation and looking forward to the second step of the project,” said Liu Wei, Overseas Regional Project Manager of Haier Group.
Brienon-sur-Armançon is a city in the Burgundy-Franche-Comté region of north-central France, with a population of about 3,300. Located at the intersection of two rivers – Créanton and 'Armançon, Brienon-sur-Armançon enjoys an advanced road network which is vulnerable to illegal activities. To make the city safer, the local government, with far less than sufficient police force at hand, chose to secure its city and residents with Dahua Safe City Solution.
There were two main pressing issues that needed to be addressed. Firstly, the city had far less than insufficient police force, only one policeman was supposed to look after the whole 3,300 dwellers. Secondly, Brienon-sur-Armançon had not prepared itself with necessary cables needed for modern surveillance systems, requiring the Dahua Team to design a tailored solution according to the unique local environment and limited human resources of this city.
Wireless transmission device
This solution aids them in obtaining video recordings that can be used as evidence in case of an incident
To make up for the shortage of police force and network cables, Dahua Technology delivered a customized solution covering the whole city with various kinds of video surveillance devices. These equipment are linked by a wireless device combining PTZ camera and antenna that transmits all the collected information to the highest point in the city center. These data are then transmitted to the control center, making it easy for the police to achieve round-the-clock monitoring.
To monitor major sections of the city, an array of modern devices were utilised including Starlight IR PTZ AI Network Camera, Multi-Sensor Panoramic Camera, Eyeball Camera, Thermal Camera, ANPR Camera, Wireless transmission device, keyboard, etc. From the control center in the police station, the police can check real-time situation and decide whether to take action. This solution also aids them in obtaining video recordings that can be used as evidence in case of an incident.
Vehicles trigger detection
In addition, the combined strength of the Dahua general camera and PTZ camera created a smart capture mechanism for the police. General cameras were installed to monitor fixed scenes, once human or vehicles trigger detection rules set by the operator (like tripwire and intrusion), the PTZ camera will automatically zoom-in and start tracking. For low-light applications, the Dahua Starlight Technology of the PTZ camera also offers outstanding light sensitivity, capturing color details even under ultra-low light condition.
Moreover, ANPR Cameras were deployed for road safety enforcement on main roads. Embedded with License Plate Recognition (LPR) algorithm, the cameras have the ability to detect and recognize moving vehicle's plate number within low speed. Furthermore, installing Thermal Cameras took care of the job of monitoring the BBQ sites in the park with their built-in fire detection functionality that can detect fires even at long range distance.
Effectively monitor major areas
The police has solved a cemetery theft case with evidence recorded by the Dahua PTZ cameraWireless transmission device made it possible for all cameras in all locations to connect to the control center without the cost and trouble of wiring. NKB 5000 HD Network Control Keyboard was installed in the control center to help the police achieve split screen operation of both general and PTZ cameras. Some Seagate hard disks were also used to store recorded videos for future use.
The Brienon-sur-Armançon police can now sit remotely in the control room and operate in an efficient way with the help of Dahua Safe City Solution, which allows them to effectively monitor major areas in the city and respond in time when an incident takes place.
Dahua PTZ camera
The recorded videos also serve as crucial evidence and help the police to crack a case with much less effort. In the first week of the test run of this smart system, the police has already solved a cemetery theft case with evidence recorded by the Dahua PTZ camera.
“The origin of our cooperation with Dahua dates back to the visit to China a year ago. This visit to the Dahua headquarters in Hangzhou concluded with a reciprocal commitment – to equip the city of Brienon with video surveillance. We welcomed this agreement, which allowed the installation of the system and improved the daily life of our residents.” said Mr. Jean-Claude M.CARRA, Mayor of Brienon-sur-Armançon.
With the opening of the new Thomson Nature Park, Singapore, the National Parks Board (NParks) recently unveiled a new system to help detect wildlife crossing the roads between forests and provide real-time warning messages for approaching vehicles, so that the vehicles can slow down and let the animals safely walk onto the other side (The Strait Times).
IronYun AI NVR Animal Detection solution
IronYun AI NVR Animal Detection is the solution that NParks has selected to realize the system
IronYun AI NVR Animal Detection is the solution that NParks has selected to realize the system. On one hand, AI NVR uses deep learning AI models to accurately recognize animals versus vehicles and people via camera feeds on the roadside. On the other hand, AI NVR integrates with signage systems to trigger the appropriate alerts when such animals are detected.
Wildlife protection program:
“Thomson Nature Park (TNP) is a 50-hectar (124-acre) green space to buffer between the eastern forests of the Central Catchment Nature Reserve and the new infrastructure developments. TNP is separated from the Nature Reserve by a 3-km-long Old Upper Thomson Road, on which visitor cars frequently travel. Animals, however, do not recognize manmade geographical boundaries”, said NParks Director for Conservation, Sharon Chan, and thus often walk across the road from the forest into TNP and vice versa to forage for foods and find mates.
Animal-vehicle collisions have occurred because the cars and motorcycles cannot see the animals and stop in time. Meanwhile, biodiversity surveys have indicated that many native animals, including critically endangered species such as the Raffles' banded langur and the Sunda pangolin often cross this road.
Several measures have been implemented to protect the animals, including:
Aerial crossing: a rope ladder and a single rope crossing along the Old Upper Thomson Road to help canopy-dwelling animals crossing overhead
Culverts: five culverts to help ground-dwelling mammals crossing underground
Reducing traffic: turning Old Upper Thomson Road from a dual-lane road to a single-lane road in June 2018; plans to close the road to vehicles between 7:30 pm – 6 am daily in the future
Roadway animal detection system: a combination of IronYun AI NVR, cameras, and signage to alert vehicles to slow down from afar when an animal crosses the road
In particular, the roadway animal detection system is co-funded by NParks and the Land Transport Authority (LTA) to reduce animal-vehicle accidents. At the heart of the system is IronYun AI NVR.
AI technology for wildlife protection
The system is guaranteed to recognize a human versus an animal versus a vehicle
AI NVR is a deep learning video analytics solution, which can distinguish several types of objects, including vehicles (car, bus, motorcycle, etc.), people, manmade objects (backpack, suitcase, etc.), and animals. IronYun engineering teams train the AI models using thousands of hours of video data to ensure high accuracy, so the benefits are two-fold:
No false alarms: the system is guaranteed to recognize a human versus an animal versus a vehicle. As an improvement compared to legacy sensor-based systems, motions caused by tree branches swaying, people walking/biking, cars driving by, etc. do not trigger any alarm. In this case, only an animal crossing the road would trigger an alarm.
Easy to use: no calibration to the environment is required. The model is pre-trained and ready to use from day 1.
AI Network Video Recorders (NVRs)
The LTA and NParks users set the alert rule so that when an animal appears, AI NVR recognizes, records the metadata and triggers lights to flash under a sign that reads ‘Animals Ahead’, all within 3 seconds. The car sees the flashing light and slows down, allowing the animals to reach safety.
The unintrusive monitoring and alert system AI NVR has proven useful
The current system supports 5 cameras along Old Upper Thomson Road. The system was announced on October 11, 2019, and is a year-long pilot project in the joint effort of LTA and NParks to protect wildlife in Singapore national parks.
Unobtrusive and alert video system
While the rope crossing and culverts help providing the animals safe alternative travel routes, Dr. Andie Ang, a primate scientist and chair of the Raffles’ Banded Langur Working Group, has commented that it would take time for animals like the Langurs to get used to artificial structures, so long-term monitoring is necessary.
Therefore, the unintrusive monitoring and alert system AI NVR has proven useful. According to LTA Chief Executive, Ngien Hoon Ping, “Joint efforts, such as the one on the roadway animal detection system, help us understand how technology could be deployed to achieve our aims.”
The new year comes with new opportunities for the security industry, but what technologies will dominate our discussions in 2020? Topics such as artificial intelligence (AI) and HCI (hyperconverged infrastructure) became familiar in conversations during 2019, and they are likely to dominate our thoughts again in the new year. But other buzzwords are also gaining steam, such as “blockchain” and “frictionless access control.” Connectivity and the cloud will also be timely technology topics as the industry evolves. We asked this week’s Expert Panel Roundtable: What technology buzz will dominate the security industry in 2020?
Public spaces provide soft targets and are often the sites of terrorist or active shooter attacks. Public spaces, by definition, require easy accessibility and unrestricted movement. Given that openness, what security technologies can provide real results? We asked this week’s Expert Panel Roundtable: How is technology innovation impacting the security of public spaces?
Video storage is an important – and expensive – aspect of almost any surveillance system. Higher camera counts equate to a need for more storage. New analytics systems make it easier for operators to manage video, but that video must be dependably stored and easy to access if and when it is needed. To keep up to date on the latest developments, we asked this week’s Expert Panel Roundtable: What’s new in video storage solutions?