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 customisable 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 customise 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 burglarised, 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 analysing 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 analyse massive amounts of data locally and identify trends is a key advantage of AI at the edge

The ability to analyse 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.

Edge cameras

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 recognise residents and then unlock their smart front door locks automatically if desired, eliminating the need for keys.

And if, for example, an unauthorised 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.

Share with LinkedIn Share with Twitter Share with Facebook Share with Facebook
Download PDF version Download PDF version

Author profile

William Xu Senior Product Marketing Manager, Ambarella, Inc.

In case you missed it

Physical security and the cloud: why one can’t work without the other
Physical security and the cloud: why one can’t work without the other

Human beings have a long-standing relationship with privacy and security. For centuries, we’ve locked our doors, held close our most precious possessions, and been wary of the threats posed by thieves. As time has gone on, our relationship with security has become more complicated as we’ve now got much more to be protective of. As technological advancements in security have got smarter and stronger, so have those looking to compromise it. Cybersecurity Cybersecurity, however, is still incredibly new to humans when we look at the long relationship that we have with security in general. As much as we understand the basics, such as keeping our passwords secure and storing data in safe places, our understanding of cybersecurity as a whole is complicated and so is our understanding of the threats that it protects against. However, the relationship between physical security and cybersecurity is often interlinked. Business leaders may find themselves weighing up the different risks to the physical security of their business. As a result, they implement CCTV into the office space, and alarms are placed on doors to help repel intruders. Importance of cybersecurity But what happens when the data that is collected from such security devices is also at risk of being stolen, and you don’t have to break through the front door of an office to get it? The answer is that your physical security can lose its power to keep your business safe if your cybersecurity is weak. As a result, cybersecurity is incredibly important to empower your physical security. We’ve seen the risks posed by cybersecurity hacks in recent news. Video security company Verkada recently suffered a security breach as malicious attackers obtained access to the contents of many of its live camera feeds, and a recent report by the UK government says two in five UK firms experienced cyberattacks in 2020. Cloud computing – The solution Cloud stores information in data centres located anywhere in the world, and is maintained by a third party Cloud computing offers a solution. The cloud stores your information in data centres located anywhere in the world and is maintained by a third party, such as Claranet. As the data sits on hosted servers, it’s easily accessible while not being at risk of being stolen through your physical device. Here’s why cloud computing can help to ensure that your physical security and the data it holds aren’t compromised. Cloud anxiety It’s completely normal to speculate whether your data is safe when it’s stored within a cloud infrastructure. As we are effectively outsourcing our security by storing our important files on servers we have no control over - and, in some cases, limited understanding of - it’s natural to worry about how vulnerable this is to cyber-attacks. The reality is, the data that you save on the cloud is likely to be a lot safer than that which you store on your device. Cyber hackers can try and trick you into clicking on links that deploy malware or pose as a help desk trying to fix your machine. As a result, they can access your device and if this is where you’re storing important security data, then it is vulnerable. Cloud service providers Cloud service providers offer security that is a lot stronger than the software in the personal computer Cloud service providers offer security that is a lot stronger than the software that is likely in place on your personal computer. Hyperscalers such as Microsoft and Amazon Web Service (AWS) are able to hire countless more security experts than any individual company - save the corporate behemoth - could afford. These major platform owners have culpability for thousands of customers on their cloud and are constantly working to enhance the security of their platforms. The security provided by cloud service providers such as Claranet is an extension of these capabilities. Cloud resistance Cloud servers are located in remote locations that workers don’t have access to. They are also encrypted, which is the process of converting information or data into code to prevent unauthorised access. Additionally, cloud infrastructure providers like ourselves look to regularly update your security to protect against viruses and malware, leaving you free to get on with your work without any niggling worries about your data being at risk from hackers. Data centres Cloud providers provide sophisticated security measures and solutions in the form of firewalls and AI Additionally, cloud providers are also able to provide sophisticated security measures and solutions in the form of firewalls and artificial intelligence, as well as data redundancy, where the same piece of data is held within several separate data centres. This is effectively super-strong backup and recovery, meaning that if a server goes down, you can access your files from a backup server. Empowering physical security with cybersecurity By storing the data gathered by your physical security in the cloud, you're not just significantly reducing the risk of cyber-attacks, but also protecting it from physical threats such as damage in the event of a fire or flood. Rather than viewing your physical and cybersecurity as two different entities, treat them as part of one system: if one is compromised, the other is also at risk. They should work in tandem to keep your whole organisation secure.

Video surveillance is getting smarter and more connected
Video surveillance is getting smarter and more connected

The global pandemic has triggered considerable innovation and change in the video surveillance sector. Last year, organisations around the globe embraced video surveillance technologies to manage social distancing, monitor occupancy levels in internal and external settings, and enhance their return-to-work processes. Forced to reimagine nearly every facet of their operations for a new post-COVID reality, companies were quick to seize on the possibilities offered by today’s next-generation video surveillance systems. Whether that was utilising motion sensing technologies to automatically close doors or switch on lighting in near-deserted office facilities. Or checking if people were wearing masks and adhering to distancing rules. Or keeping a watchful eye on streets and public spaces during mandated curfew hours. Beyond surveillance and monitoring use cases, organisations also took advantage of a raft of new Artificial Intelligence (AI) applications to undertake a range of tasks. Everything from automating their building management and optimising warehouse operations, to increasing manufacturing output and undertaking predictive maintenance. Behind the scenes, three key trends all contributed to the growing ubiquity of video surveillance observed in a variety of government, healthcare, corporate, retail, and industry settings. Video surveillance takes to the Cloud Last year the shift to digital working led organisations to rapidly embrace cloud-enabled services, including cloud-hosted Video Surveillance As A Service (VSaaS) solutions that provide tremendous economies of scale and flexibility. Alongside significant cost savings, these solutions make it easier for organisations to enhance their disaster recovery and manage their video surveillance estate in new and highly effective ways. Surveillance cameras with audio recording were used more than 200% by customers between 2016 and 2020For example, in addition to enabling remote access and maintenance, today’s cloud-powered systems eliminate any need to invest in local storage technologies that all too often fail to keep pace with an organisation’s growing data storage requirements. Indeed, data from our worldwide customer base survey reveals how in 2020 an impressive 63% of organisations had abandoned using any on-premises storage option and were instead only storing all their video surveillance recordings and data in the Cloud. A deeper review of the global stats shows that the average cloud recording retention period for this stored data was 28.2 days, with organisations in Asia topping the global average at 38 days – 33% higher than was observed in any other region. Improvements in bandwidth and scalability engendered by the Cloud have also helped boost the growing utilisation of audio recordings in addition to visual image capture. Indeed, our research found the number of surveillance cameras with an audio recording facility used by customers jumped more than 200% between 2016 and 2020. Making sense of Big Data The enhanced ease of connectivity and scalable bandwidth made possible by the Cloud is stimulating more companies to connect a lot more video surveillance cameras to their networks. The top motivation for doing so is to generate live metrics and data that can be utilised to deliver enhanced business insights and operational intelligence. In recent years, a rich choice of video analytics solutions have been developed for a variety of industry verticals. The range of functionalities on offer is impressive and covers a variety of applications. Everything from making it easy to classify and track objects and behaviour patterns in real-time, to undertaking anomaly detection, or generating predictions based on past and present events/activities. Data collected via today’s cloud connected cameras can now also be used to feed deep learning training and AI analytics, utilising the unparalleled virtualised processing capacity of the Cloud to convert Big Data into usable information quickly. By integrating this information with data from other enterprise data capture systems, organisations are now able to gain a 360-degree view of their operations – in almost real-time. IT is now in the driving seat No longer the sole preserve of on-site security staff, the wider application and business use of video surveillance means that IT is increasingly taking the lead role where the management and control of these systems are concerned. IT is asked to integrate video surveillance into key enterprise platforms to generate the data that business leaders need Aside from the fact that IT has a vested interest in addressing the cybersecurity implications that come with attaching a growing range of IoT devices to the enterprise network, they’re also increasingly being asked to integrate video surveillance into key enterprise platforms to generate the data that business leaders need. As organisations expand their integration of video with other business applications, such as point of sale, access control, process control and manufacturing systems, this trend is only set to accelerate. Looking to the future Right now, the video surveillance industry is at a key tipping point, as video systems become increasingly strategic for enabling the enterprise to boost productivity, stay compliant, and fulfil its obligations to protect employees and customers. As the technology’s contribution to enhanced data-driven decision-making and problem solving continues to increase, expect the adoption of IP connected video cameras to burgeon as organisations look to capture more data from their day-to-day business operations.

How has Brexit affected the security industry?
How has Brexit affected the security industry?

When the United Kingdom voted to leave the European Union, a world of uncertainty unfolded for those doing business in the UK and the EU. The referendum was passed in July 2016. Including subsequent delays, the separation was completed after four years in January 2020, with a transition period ending December 2020. Even with the deadlines past, there are still pockets of uncertainty stemming from the separation. We asked this week’s Expert Panel Roundtable: How has Brexit affected the security industry?