New technologies for capturing more data are leading to a heightened need for education on how to effectively manage data storage and bandwidth, says Aaron Saks, Senior Technical Marketing and Training Manager at Hanwha Vision America.
Data usage is becoming more prevalent across all areas of security and surveillance.
Organizations are increasingly realizing the value in harnessing the data already being generated by camera analytics and using it to derive actionable insights and make informed business decisions.
This reliance on data creates clear benefits for security professionals, but at the same time uncovers immediate challenges.
With more data flying around, how can security teams get a handle on effective data storage so it can be useful without becoming unwieldy?
To find the answer, it’s first important to understand the trends leading to our industry’s increasing reliance on data, as well as the developments in technology related to new capabilities for data storage and bandwidth management.
Current cameras are able to capture more footage in higher resolutions. While these cameras provide unparalleled clarity and detail, they also generate massive amounts of data, often straining data storage infrastructures and requiring higher bandwidth for real-time streaming and analysis.
Additionally, the industry is witnessing a shift toward more efficient compression algorithms and advanced storage solutions to cope with escalating data volumes.
The emergence of edge computing is helping by revolutionizing the way security and surveillance data is processed and stored.
Instead of relying solely on centralized data centers, edge computing involves processing data closer to the source, reducing latency and alleviating bandwidth constraints.
Also, the type of data storage and bandwidth management needed often depends on an individual organization’s requirements.
Often, cloud deployments make sense for operations with small surveillance systems.
For example, it might be a small to medium-sized business, maybe a local restaurant with only up to eight cameras.
That location wouldn’t need a large server or massive data storage space since they don’t have significant demands on their system and don’t have a server rack for a network video recorder (NVR).
For them, a system that is either direct-to-cloud where it’s just cameras or a hybrid system where there’s an on-site gateway works perfectly for them.
All that’s needed is a compact box that could sit in a back office or under the counter by the register.
This type of gateway allows data to be stored locally in case of internet issues and also offers the ability to enhance bandwidth based on time of day.
When it comes to managing bandwidth and data storage considerations, many users find that the most significant benefits associated with the cloud are its flexibility, elasticity and ability to scale seamlessly to an operation’s needs and resources.
An operation may be recording 30 days currently, but in a few months or seasonally it may need to record for a period of 60 days.
An operator can log in remotely and in a few clicks, make an update without having to go on site and change out hard drives.
A properly configured cloud system should have its own data centers and not be running on “general purpose” existing clouds.
They should have data centers in the customer’s country to ensure compliance with any data protection laws, as well as to ensure the best performance.
The data should replicate to multiple data centers and it should also be encrypted in transit and at rest.
Another important consideration is that no one – not even the cloud provider – should have access to the video, except for the customer and possibly the integrator, if granted access.
As the volume of surveillance data continues to soar, organizations are exploring hybrid cloud solutions to address data storage scalability and accessibility issues.
Hybrid cloud architectures allow the seamless integration of on-premise data storage with cloud services, providing flexibility and cost-efficiency.
There are many applications that can dictate when a hybrid approach makes sense.
For example, in many markets such as cannabis or banking, there are regulations stating that operations must have both on-site and off-site back-up storage.
Hybrid configurations enable the flexibility to have full on-site video recording capability combined with a full cloud user interface with all the necessary features and functionality without tying up network bandwidth.
It’s a different issue when operations have large systems with hundreds of cameras.
Then data storage management can get unwieldy in terms of the number of gateways and bandwidth needed.
In that type of scenario, a traditional on-prem system often makes more sense since it’s not necessary to send all data to the cloud all the time.
Hybrid systems provide the best of both worlds. Essentially, an operation can “mix and match” and go either way.
In the coming months and years, we’ll see much more blending of on-prem systems with cloud backup or cloud archiving, with more customers embracing the idea of picking and choosing and only paying for the cloud services they need.
The continued integration of AI and machine learning in security and surveillance systems has enabled smart video analytics, automated threat detection and predictive analysis.
Depending on the environment and activity in surrounding areas, an organization may need to consider the factor of “unnecessary information” when it comes to AI analytics to detect and track motion.
A security team only needs to know if something comes over the perimeter or enters the grounds, but the elements on the outside usually aren’t that useful.
For example, if there are many waving trees along a perimeter or surrounding a building, then those environmental factors may trigger false alarms.
Heavily wooded areas versus open areas could also be factors in determining context.
Often, security teams don’t care much about trees swaying in the wind since they’re likely more focused on the fence line or only want to see people walking inside the perimeter.
That’s where AI-based analytics are beneficial. Surveillance camera operators can easily get bombarded with too much information – and too many false event alarms – especially if they’re using conventional cameras equipped with motion-based pixel detection.
AI and deep learning algorithms detect and classify distinct objects (people, vehicles, faces and license plates) while clearly distinguishing them from their environmental surroundings.
These types of “smart” cameras filter out irrelevant motion triggers to focus only on people, objects and vehicles and generate only the events users need to see for effective forensic searches and enhanced operational efficiency.
As a result, they also minimize data storage and bandwidth by not tracking and recording every type of object in motion.
AI-based “smart” compression and noise reduction technologies are growing in use.
They can say to a user: “Here’s this high-resolution camera footage, do you want to reduce bandwidth and manipulate the compression based on the objects we care about?”
This level of context awareness takes AI beyond the level of pre-configured algorithms. It lets a system gather information about its environment and adapt its behavior accordingly.
Now, the camera is making choices to optimize its performance based on what it has learned in the past and what is important to the user.
Through ongoing firmware updates, newer cameras are able to take targeted AI detection and internally adjust what the camera is doing – again, using context awareness.
It’s the next phase of “smart” data storage and bandwidth management where the technology continually learns to help users make better informed decisions.
The only real certainty in our industry is that technology will continue to evolve and staying ahead of the curve in data storage and bandwidth management will be crucial for organizations with the objective of providing forward-looking security and surveillance solutions.
This article was originally published in the November edition of Security Journal Americas. To read your FREE digital edition, click here.