In the previous comparison of Cloud and Ip cameras, here, we mainly touched upon the differences from the user perspective. In this article, we will delve bit deeper into how Cloud camera technology is different than the Ip camera technology. You need to be familiar with networking and bit of cloud.

Ip Cameras are passive devices that can be accessed from an IP-address. There are a variety of ways you can configure an IP camera or any other IP based device to connect to a wifi network. Once connected to the local wifi network, in technical terms the IP camera is now connected to your local infrastructure network and is available on a particular IP address, assigned manually or picked up automatically(using DHCP). If you need to access this device on internet remotely then you will have to make the IP visible to external networks by port forwarding or making it part of DMZ. Some of the IP cameras may allow you to configure online storage in terms of FTP locations, but they will not be able to maintain the storage and you will be responsible for keeping the usage under check. In case you plan to deploy many such cameras in your business premises the maintenance overhead increases, you will need to add sd-cards or configure online storage in all of them. Figure out different ports where the IP will be forwarded for internet access. In the end, it is too much hassle to run and manage many such cameras.

Cloud cameras extend the functionality of the IP cameras. Cloud cameras are proactive devices that interact with the cloud for storage, alerts, management, and analytics. Some of the things we are going to talk about now will be mainly in the backdrop of our ibeyonde cloud camera technology. So if you need a single camera then IP camera is good as there are not that high management overheads. In contrast, even a small business that requires 8 cameras cannot afford the overhead of managing IP cameras. Cloud cameras solve this neatly. Managing multiple devices is easy, you get a unified view into these devices from your online account. All the functionality like live viewing, alerting, analytics, browsing history, and history tagging are available thru all the major browsers and mobile apps.

Since Cloud cameras are built for mass deployment, that is why the security of the data is part and parcel of the system. There are user authentication and authorization. The channel thru which data passes is secured using industrial grade security. Devices use security tokens to get authenticated and encrypt any sensitive information.

The surveillance data that is captured by cloud cameras is channeled thru cloud where there is a choice of running AI micro-services on the channel. Ibeyonde provides many AI and ML algorithms that constitute the micro-services that can be subscribed to and enabled on the surveillance data that is being channeled thru the cloud servers. So now you have a cloud camera installed at the factory entrance that can recognize license plate numbers and gives you text search capability on these recognized number plates. You have cloud camera in the elevator that gives you feedback on how crowded they are. And you have a cloud camera on the entrance keeping away bad people using facial recognition. And a cloud camera in the restaurant that can tell you what dishes make people happy. And a cloud camera in the mall filing faces that actually make a purchase. And you can now take a guess on the possibilities.

So now that we see how a single camera can be converted to cater to a specific purpose, with cloud we can make the grid of cloud cameras even more useful. What if your camera can figure out what kind of location it is, whether there are other cameras in the proximity. If it can, then the possibilities reach another level of sophistication altogether. You have multiple entrances to your secured premises, the cameras on entrances pool their resources to keep a tab of how many people have entered versus how many people have left the premises. The cloud cameras can combine this collective intelligence. ¬†This can let you track the movement of a suspected person across cloud cameras. There is a smart template search engine that let you search for specific patterns across several cameras. A group of cameras who can learn their proximity to other cameras can pool their surveillance data and automatically create ‘events’ that span across cameras. Ibeyonde cameras form a smart grid from a set of cloud cameras installed in proximity to each other, this grid then detects events that involved one and more of these cameras and add them to your events tab. All of this is part of cloud cameras self-learning and no manual intervention is required, other than logging in viewing nicely organized data.

The Ibeyonde cloud cameras are also analyzing your surveillance data and making a custom event model out of it. Anything unusual that happens and that is not conforming to this model is flagged as an unusual event. It could be the person going around at the unusual time or something happening in part of the camera view that is least expected.

The Ibeyonde cloud camera API gives you API level access to many of the cloud camera features, configuration, and functions. This makes integrating camera functions with access control system, visitor management systems and others.

Once your live video feed from a cloud camera is going to cloud servers, it can be broadcasted, or it can be recorded and archived to be played later.

The storage of the historical records is also managed by cloud services. You just need to specify how much history you want to store on the cloud and yes this is not free but also not prohibitive.