As security cameras have proliferated in the workplace, managing security systems has transitioned from being a one-time set-and-forget for IT to an ongoing commitment.
IT professionals are bogged down with requests to retrieve video and root causing system downtime across a patchwork of systems across locations. And as the need to access and retrieve video increases in frequency, these demands on IT are only intensifying.
This is making the choice of the right camera system even more critical.
{{WEBINAR_BANNER}}
What to think about when choosing your new camera system
When evaluating and choosing your new camera system, there are many requirements for an organization. From set-up to implementation and feature velocity, making the right choice is critical for success.
Meet the minimum requirements of a modern system
Cloud is table stakes in video surveillance today. This encompasses easy remote viewing across locations, easy search and collaboration, and best-in-class cybersecurity. Most organizations maintain their video surveillance systems for three to five years. You need to ensure that your new camera system will stay relevant and updated throughout the duration of your contract.
Evaluate feature velocity of the vendors you want to partner with
The current pace of AI development is unprecedented, with new features and products launching weekly. This means that a product that has a unique set of features today, may not be as interesting in the near future. When selecting your next system, it’s important to select one that has a proven track record of high feature velocity. This is important so that your organization can keep up with the rapid pace of AI development.
Users will be able to benefit more quickly from new features and will become a compounding advantage over the life of the camera system. This means your camera system can become an appreciating assets rather than a cost center.
Proactively evaluate the health of your networks
As more users want to do more with video footage, your network utilization may rise.
You may run into bandwidth constraints if your system of choice of bandwidth consumptive. Your data is also at risk of being exposed to malicious actors if not properly protected..To evaluate the health of your networks, ask questions like:
- Do we have sufficient bandwidth for our video workflows today?
- Are there unexpected data flows or unusually high bandwidth consumption observed in the surveillance system traffic?
- How often do unauthorized devices attempt to access the network?
Have the observability to easily manage your systems across locations
As your organization grows, managing the network and connected devices becomes more and more complex. Observability into network health is a crucial aspect of network management and monitoring.
Best-in-class video surveillance systems can provide insights into the health of the surveillance system’s components, such as cameras, recorders, and network infrastructure. This information helps in planning maintenance and replacing or upgrading components as needed to avoid unexpected failures.
Observability can help in monitoring the health of individual cameras, ensuring they are functioning correctly. Additionally, user management is a critical component of IT and information security, particularly in organizations that rely on digital systems and networks.
This ensures easy provisioning and modification of access for employees, contractors, and other users.
Finding the hidden costs in your next camera system
Whether choosing cloud cameras, cloud NVR, or an AI Camera System, understanding total cost of ownership (TCO) and what possible costs are involved is critical in making the right short term and long term decision.
Cameras
Depending on the type of camera system you choose, cameras may or may not be included. Some vendors will require you to purchase proprietary cameras at higher costs. Other vendors like those who offer an AI Camera System are generally vendor agnostic, meaning you can use almost any IP camera using RTSP/ONVIF protocols.
TCO implications: Immediate and future camera replacements baked into the choice of system
Local storage
Your camera system can have varying degrees of TCO depending on local storage. Cloud cameras, for example, use more expensive on-board flash memory storage. At higher camera counts, TCO will surpass a cloud NVR-based solution.
Cloud NVRs have local storage on HDDs, which is more cost effective. At higher camera counts, this is more likely to be cost effective than cloud cameras.
AI Camera Systems provides local storage on HDDs and is cost effective. AI Camera Systems are likely to be more cost-effective at higher camera counts.
TCO implications: Relative costs of storage, especially at higher camera counts
Software
Cloud cameras and AI Camera Systems provide easy-to-use software with little or no training required. Cloud NVRs are different than Cloud cameras or AI Camera Systems because they can have unintuitive user interfaces that can require additional training and ongoing support from IT teams.
TCO implications: Resources required for end-user adoption. Products that are difficult to use are likely to require initial and ongoing IT support.
AI capabilities
Cloud cameras and Cloud NVRs will have some limited AI capabilities, and not all of them will be out of the box. Some of the AI capabilities for cloud cameras and cloud NVRs include:
- Motion detection
- People detection
- Vehicle detection
AI Camera Systems provide robust AI capabilities out of the box. Hybrid AI enables features to be more powerful, more useful, and more response.
Some of the AI capabilities for an AI Camera System include:
- Motion detection
- People detection
- Vehicle detection
- Facial recognition
- License plate recognition
- AI assistants
TCO implications: Cost of ongoing upgrades to keep up with the latest and greatest in AI over the life of the system.
Network and bandwidth
Customers using cloud cameras may need to upgrade their network infrastructure to support video consumption requirements if they are in limited bandwidth areas.
Cloud NVRs may not need to upgrade network infrastructure to support video as long as an organization isn’t looking to use robust AI capabilities like AI assistants.
With an AI Camera System, customers in limited bandwidth areas may not need to upgrade network infrastructure to support video consumption requirements even for advanced AI use cases.
TCO implications: Network/SD-WAN upgrades required to deliver desired user experience and functionality.
Installation
Cloud cameras will require all cameras to replaced. One they are replaced, setup is generally easy. With Cloud NVRs, cameras may not need to be replaced but NVR installation will require access to the local network.
AI Camera Systems do not require camera replacements. Intelligent Video Recorder (IVR) will require access to the local network.
TCO implications: Total cost of setup including installation of cameras, setup, and configuration of equipment
Post-sales support and warranty
Defects can arise in the best of products, and cloud cameras may stop working over the life of the contract. Some vendors offer 10-year warranties on cameras.
Cloud NVR vendors usually offer a warranty for the life of the contract. Some vendors don’t charge separately for ongoing support.
AI Camera System vendors usually offer warranty for the life of the contract. Some vendors don’t charge separately for ongoing support.
TCO implications: Warranty on hardware. Additional cost of support based on vendor/VAR agreement.
Ready to learn more? Get started today.
