As mentioned previously, in addition to the onboard storage available on every camera, Meraki also offers a Cloud Archive option with the purchase of an additional license that allows video to be automatically backed up to a secure, offsite cloud storage location for extended retention. This feature provides the additional retention options offered by a traditional surveillance system while reducing the need for additional onsite infrastructure and hardware. Selecting Meraki Cloud Archive for your video storage needs brings numerous advantages:

Scalability: Meraki Cloud Archive offers scalable storage options, allowing you to effortlessly expand capacity as your requirements grow.

Simplified management: With Meraki Cloud Archive, video storage and management seamlessly integrate into the Dashboard.

Redundancy and reliability: Storing video footage in the cloud eliminates the risk of data loss due to local hardware failures or accidents.

Cost-effectiveness: Meraki Cloud Archive eliminates the need for on-premises storage infrastructure, reducing upfront capital expenditure and ongoing maintenance costs. You can choose from different storage plans based on your retention requirements, optimizing costs according to your specific needs.

Security and compliance: Meraki’s cloud infrastructure provides robust security measures to protect your video footage, including encryption and access controls. This ensures compliance with data protection regulations and safeguards sensitive information.

When using Cloud Archive, both the camera and the cloud maintain copies of the video, and the on-camera recording remains unchanged. Videos stored in the cloud are consistently in the form of continuous 24/7 footage.

In terms of video retrieval, the Dashboard gives priority to video stored locally on the related camera, unless the camera is unreachable from the cloud or the requested video’s timestamp exceeds the available local storage. Even if the camera temporarily loses connection to the cloud, it will still record footage as long as it has power, although the footage will not be backed up to the cloud until the camera regains WAN/cloud connectivity.

Accessing Video Event Logs

The video access log contains the record of all video access–related actions for all cameras within a network and external stream users. To access the video access logs, navigate to Cameras > Video Access > Video Access Log on the Dashboard (see Figure 9-44).

Figure 9-44 Reviewing the Video Access Log

Click the External Stream Users tab (see Figure 9-45) to view a list of all users who have shared live stream links and the expiration status of those links.

Figure 9-45 Reviewing Access Logs for External Stream Shares

For more information on sharing video clips or a video stream from both the video wall or the camera status page, search https://documentation.meraki.com using the keywords Sharing Video.

Meraki MV Sense

As previously discussed, Meraki cameras have built-in capabilities to detect people, vehicles, and motion. With the MV Sense feature, you can utilize Custom Computer Vision (Custom CV) to deploy and execute custom machine learning (ML) models directly on MV cameras, enabling them to learn and perform custom object detection.

One of the foundational capabilities of MV Sense is its ability to use artifacts, which are essentially ML models. These models can be uploaded directly to the MV camera via the Dashboard. Once provisioned, the camera becomes a source of intelligent data. Figure 9-46 illustrates the high-level architecture of Meraki MV Sense.

Figure 9-46 MV Sense Architecture

MV Sense utilizes several aspects of the MV camera system to perform these functions:

Edge processing: MV Sense harnesses the raw computational power of the MV camera’s onboard processors. Instead of sending data to a central server for analysis, the camera analyzes the data at the source. This edge processing ensures faster response times, reduced network congestion, and more efficient operation.

MQTT for telemetry: Using MQTT, a lightweight messaging protocol, MV Sense ensures that data transmission between the camera and other systems is efficient and rapid. This is particularly useful in IoT environments where real-time data exchange is crucial.

Versatile ML models: When equipped with MV Sense, the MV camera can understand and interpret multiple ML models simultaneously. This means it can concurrently detect people, vehicles, motion, and more, adapting its insights according to the specific ML model in use. This multifaceted detection capability opens up many applications, from monitoring foot traffic in retail environments to optimizing parking solutions in urban settings.

Enabling the MV Sense feature set further enhances security and becomes a valuable tool for businesses seeking insights into their operational environments. It directly showcases the vast potential of integrating advanced machine-learning capabilities into surveillance systems.

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