OpenVisualCloud/Smart-City-Sample

The E2E sample implements aspects of smart city sensing, analytics and management features as follows:

Camera Provisioning: Tag and calibrate cameras for installation locations, calibration parameters and other usage pattern information.
Camera Discovery: Discover and register IP cameras on specified IP blocks. Registered cameras automatically participate into the analytics activities. See Sensor Simulation and Discovery for additional details.
Recording: Record and manage segmented camera footage for preview or review (at a later time) purpose.
Analytics: Perform analytics on the live/recorded camera streams. Latency-sensitive analytics are performed on Edge while others are on cloud.
Triggers and Alerts: Manage triggers on analytics data. Respond with actions on triggered alerts.
Smart Upload and Archive: Transcode and upload only critical data to cloud for archival or further offline analysis.
Stats: Calculate statistics for planning/monitoring purpose on analytical data.
UI: Present above data to users/administrators/city planners.

Scenarios

The sample implements the Smart-City traffic and stadium scenarios. The traffic scenario measures vehicle/pedestrian flow for planning purpose. The stadium scenario focuses on different access control techniques, including entrance people counting, service-point queue counting, and stadium seating zone crowd counting.

Traffic	Stadium

Software Stacks

The sample is powered by the following Open Visual Cloud software stacks:

Edge Low-latency Analytics:
- The GStreamer-based media analytics stack is used for object detection, people-counting, queue-counting and crowd-counting on camera streams. The software stack is optimized for Intel® Xeon® Scalable Processors.

Smart Upload with Transcoding:
- The FFmpeg-based media transcoding stack is used to transcode recorded content before uploading to cloud. The software stack is optimized for Intel Xeon Scalable Processors.

Install Prerequisites:

Time Zone: Check that the timezone setting of your host machine is correctly configured. Timezone is used during build. If you plan to run the sample on a cluster of machines managed by Docker Swarm or Kubernetes, please make sure to synchronize time among the manager/master node and worker nodes.
Build Tools: Install cmake, make, m4, wget and gawk if they are not available on your system.
Docker Engine:
- Install docker engine. Minimum version required: 17.05. Make sure you setup docker to run as a regular user.
- Setup docker swarm, if you plan to deploy through docker swarm. See Docker Swarm Setup for additional setup details.
- Setup Kubernetes, if you plan to deploy through Kubernetes. See Kubernetes Setup for additional setup details.
- Setup docker proxy as follows if you are behind a firewall:

sudo mkdir -p /etc/systemd/system/docker.service.d       
printf "[Service]\nEnvironment=\"HTTPS_PROXY=$https_proxy\" \"NO_PROXY=$no_proxy\"\n" | sudo tee /etc/systemd/system/docker.service.d/proxy.conf       
sudo systemctl daemon-reload          
sudo systemctl restart docker

Build Sample:

Use the following commands to build the sample. By default, the sample builds to the traffic scenario. To enable the stadium scenario, use cmake -DSCENARIO=stadium ... See also: Build Options.

mkdir build    
cd build     
cmake ..    
make

Start/stop Sample:

Use the following commands to start/stop services via docker swarm:

make update # optional for private registry
make start_docker_swarm      
make stop_docker_swarm

Launch Sample UI:

Launch your browser and browse to https://<hostname> for the sample UI.

For Kubernetes/Docker Swarm, <hostname> is the hostname of the manager/master node.
If you see a browser warning of self-signed certificate, please accept it to proceed to the sample UI.