Discover Meraki APIs for Location Analytics, Cameras, and Network Health

Meraki wireless networks and security cameras are deployed in large numbers of retail outlets, hotels, campuses, and enterprises. Meraki wireless networks connect many business-critical devices, including Point-of-Sales devices, and provide internet connectivity to visiting customers. The Meraki camera provides reliable security with local and remote live viewing capabilities from Meraki cloud hosted dashboard. Both are very easy to deploy, configure, and manage via a centralized cloud management dashboard.

Meraki wireless access points and security cameras, beyond their basic functionalities, also provide valuable insight into foot traffic and behavior patterns of users. Meraki Access point collects user location information from nearby smart devices, enabling location-based analytics.

Meraki camera utilizes a powerful onboard processor to analyze video and provides valuable foot traffic insights by detecting persons using computer vision. Location insights provided by these Meraki devices enables businesses to provide better customer engagements, increase retail store traffic, and drive revenue. Meraki network location analytics and camera analytics are exposed to business owners via an easy to use Meraki dashboard.

As Meraki wireless network is enabling core business capabilities, monitoring of network health and maintaining low network latency becomes very critical to the operations team. Meraki Wireless Health features simplifies monitoring and root cause analysis of issues for all connected clients from the Meraki health dashboard. The dashboard provides a snapshot view for 1 hour, 12 hours, 1 day, and 1-week durations, along with various drill down capabilities to help identify issues.

Rich APIs for location analytics, health, and camera

Meraki pre-built dashboards for location analytics, camera analytics, and health monitoring are very useful and sufficient for many organizations. But some organizations have more advance use cases and want to retain granular data for longer periods of time. Historical data from Meraki, when combined with other business related data like Point-of-Sale, can provide very useful business insights. To enable these advanced use cases Meraki also supports rich APIs for location analytics, health, and camera analytics. These data sets can help business solve complex use-cases like:

• How much do foot traffic and sales increase during promotions?
• What is typical queue size on cash registers during specific hours of day?
• How many devices successfully connected (or failed to connect) to the network in specific locations throughout the business?

 

Merakibeat Plugin collects data from the Meraki API and stores it in an analytics database

The DevNet and Meraki teams worked together to create the Merakibeat plugin, data pipeline, and reporting dashboard based on open source technologies like Elastic Beats, Elasticsearch, and Kibana. The Merakibeat plugin enables consumption of data from Meraki wireless health, location analytics, and camera API, and stores this data in an analytics database like Elasticsearch.

Key open source components for data pipeline include:

• Elastic Beats is an open source platform for data shipper. The lightweight beats agent sends metrics to Elasticsearch. Beats is very flexible framework that supports pluggable input-output plugins.
• Merakibeat is a DevNet community contributed input plugin that can write data to any of the Beats supported output data sources like Elasticsearch, Kafka, MongoDB, Redis etc. (complete list)
• Elasticsearch is an analytics data store that saves historical data for further analysis and reporting.
• Kibana is a visualization tool for Elasticsearch, that enables creating custom reports and dashboards.
• Business metrics, like point-of-sale data, can also be ingested into the same analytics datastore to enable data analysis of business metrics, network health, and location analytics.

The DevNet team, working with Meraki engineers, developed a custom Beats plugin and reference data pipeline for Meraki APIs. This Merakibeat plugin has three sub modules –

• Meraki Health API module polls health APIs at configured intervals and fetches connection and latency status at network, device, and client levels. Polling interval and metrics to be collected can be configured using a config file.
• Location analytics scanning API supports pushing location analytics metrics to registered endpoints. The Merakibeat plugin starts a listener that accepts scanning data posted on a callback hook. The user needs to expose scanner data endpoint on external network and register callback endpoint in Meraki dashboard.
• Camera API: The Merakibeat camera module polls camera APIs at configured intervals and fetches average count of user presence and entrances in specific camera zones or full camera view.

Kibana is configured as a visualization tool for Elasticsearch, and we created a custom dashboard for wireless health status reporting. The dashboard shows different charts, like average success/failure ratios and network latencies. These charts can be viewed for various time duration (like 1day, 1week, 1month etc.) or specific date/time ranges. The Merakibeat GitHub repo also includes pre-created dashboards for Kibana that can be easily customized for user’s requirements.

To ease deployment, we bundled all components of the pipeline as Docker images, and created a Docker compose project that allows you to bring up a complete pipeline in a single command.

Merakibeat trial deployments

With one of our retail customers we deployed a trial version of Merakibeat, configured to collect wireless health and location analytics data. We also collected daily sales data from the retailer’s point-of-sale system. That enabled analyzing network health, active connections, and foot traffic with daily sales at the retail store. After collecting data for a couple of weeks we are able to create a dashboard in Kibana that helped the customer to analyze the following:

• Average number of customers visited per day
• Peak hours when customer visited retail area
• Correlation chart between customer count and sales revenue
• Percentage/count of customer devices that failed or succeed to connect wireless network

With the Cisco Merchandise Store in San Jose we deployed Merakibeat trial version configured to collect Meraki camera analytics data. After collecting data for more than a week we created a custom dashboard and alerting solution to support the following use cases:

• Overall customer store visits
• Customers queue size at cash register
• Number of customers visiting specific areas in store (e.g., apparel, gadgets, greeting cards, etc.)
• Alerts to staff via Webex Teams if a suspicious person is detected in off-hours, or queue size is greater than an established threshold

The Merakibeat plugin source is available on DevNet Code Exchange, and is also contributed to the Elastic Beats community

To get started, try the Merakibeat plugin learning lab, with step-by-step guide.

With the Merakibeat plugin project we have not only enabled specific use-cases but created a reference data pipeline to enable correlating business metrics with various Meraki API provided data. We are looking forward to see interesting analytics and reporting use cases that users will create based on data collected and made available by Merakibeat plugin.