Wireless Network-Ready Intelligent Traffic Management Reference Implementation

ID 736460
Updated 7/26/2022
Version 5.0.0
Public

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Overview 

Wireless Network-Ready Intelligent Traffic Management is designed to detect and track vehicles and pedestrians and provides the intelligence required to estimate a safety metric for an intersection. In addition, the Intel® Smart Edge Open toolkit included in the reference implementation could be used to host a 5G radio access network (RAN) on the same edge device when implemented on a platform supporting a 5G RAN.

Vehicles, motorcyclists, bicyclists and pedestrians are detected and located in video frames via object detection deep learning modules. Object tracking recognizes the same object detected across successive frames, giving the ability to estimate trajectories and speeds of the objects. The reference implementation automatically detects collisions and near-miss collisions. A real-time dashboard visualizes the intelligence extracted from the traffic intersection along with annotated video stream(s).

This collected intelligence can be used to adjust traffic light cycling to optimize the traffic flow of the intersection in near real time, or to evaluate and enhance the safety of the intersection. For example, emergency services notifications, i.e, 911 calls, could be triggered by collision detection, reducing emergency response times. Intersections with higher numbers of collisions and near-miss collision detections could be flagged for authority's attention as high-risk intersections.

The data from the traffic cameras in the intersection can be routed easily using the Intel® Smart Edge Open high-speed data plane for near-real time video analytics in the field. Further, SmartEdge-Open helps to build and manage the infrastructure to deploy, monitor, and orchestrate virtualized applications across multiple edge devices.

To run the reference implementation, you will need to first download and install the Intel® Smart Edge Open Private Wireless Experience Kit.

  • Time to Complete: 20 - 25 minutes

  • Programming Language: Python*

  • Software:

    • Intel® Distribution of OpenVINO™ toolkit 2021 Release

    • Intel® Smart Edge Open 22.04 Private Wireless Experience Kit Release

Target System Requirements

Edge Controller

  • One of the following processors:

    • Intel® Xeon® Scalable processor.

    • Intel® Xeon® Processor D.

  • At least 64 GB RAM.

  • At least 256 GB hard drive.

  • An Internet connection.

  • CentOS* 7.9.2009.

  • IP camera or pre-recorded video(s).

Edge Nodes

  • One of the following processors:

    • Intel® Xeon® Scalable processor.

    • Intel® Xeon® Processor D.

  • At least 64 GB RAM.

  • At least 256 GB hard drive.

  • An Internet connection.

  • CentOS* 7.9.2009.

  • IP camera or pre-recorded video(s).

How It Works

The application uses the inference engine and the Intel® Deep Learning Streamer (Intel® DL Streamer). The solution is designed to detect and track vehicles and pedestrians by using Intel® Smart Edge Open Private Wireless Experience Kit.

How it works diagram
Figure 1: How It Works

 

The Wireless Network-Ready application requires the application pod, database and a visualizer. Once the installation is successful, the application is ready to be deployed using helm. After the deployment, the application pod takes in the virtual/real RTSP stream addresses and performs inference and sends metadata for each stream to the InfluxDB* database. The visualizer in parallel shows the analysis over the metadata like pedestrians detected, observed collisions and processed video feed.

The application has capability to perform inferences over as much as 20 channels. In addition, the visualizer is capable to show each feed separately as well as all the feeds at the same time using Grafana*. The user can visualize the output remotely over a browser, provided that they are in same network.

 

Architecture Diagram
Figure 2: Architecture Diagram

 

Get Started

Prerequisites

To run the reference implementation, you will need to first download and install the Intel® Smart Edge Open Private Wireless Experience Kit.

Ensure that the following conditions are met properly to ensure a smooth installation process for a reference implementation done through Edge Software Provisioner (ESP) Intel® Smart Edge Open Private Wireless Experience Kit package.

  1. Hardware Requirements

    Make sure you have a fresh CentOS* 7.9.2009 installation with the Hardware specified in the Target System Requirements section.

Step 1: Install the Reference Implementation

NOTE: The following sections may use <Controller_IP> in a URL or command. Make note of your Edge Controller’s IP address and substitute it in these instructions.

 

Select Configure & Download to download the reference implementation and then follow the steps below to install it.

Configure & Download

  1. Make sure that the Target System Requirements are met properly before proceeding further.

  2. If you are behind a proxy network, be sure that proxy addresses are configured in the system:

    export http_proxy=proxy-address:proxy-port
export https_proxy=proxy-address:proxy-port

  3. Under the user deploy PWEK, for example smartedge-open, download ITM RI package:

    mkdir path-of-downloaded-directory

  4. Open a new terminal and move the downloaded .zip package to the /home/smartedge-open folder:

    mv path-of-downloaded-directory/wireless_network_ready_intelligent_traffic_management.zip /home/smartedge-open

  5. Go to the /home/smartedge-open directory using the following command and unzip the RI:

    cd /home/smartedge-open
unzip wireless_network_ready_intelligent_traffic_management.zip

  6. Go to the wireless_network_ready_intelligent_traffic_management/ directory:

    cd wireless_network_ready_intelligent_traffic_management

  7. Change permissions of the executable edgesoftware file to enable execution:

    chmod +x edgesoftware

  8. Run the command below to install the Reference Implementation:

    ./edgesoftware install

    NOTE: Installation logs are available at path:
    /var/log/esb-cli/Wireless_NetworkReady_Intelligent_Traffic_Management_<version>/<Component_Name>/install.log 

     

  9. When the installation is complete, you see the message “Installation of package complete” and the installation status for each module.
     

    Screenshot of install success
    Figure 3: Successful Installation

     

  10. Check the ITM images with the command:

    docker images

     

    Screenshot of images command output
    Figure 4: Check Images



     

Step 2: Install the ITM Application

  1. Apply the Network Attachment Definition using the provided net-sriov-itm.yaml file:

    cd wireless_network_ready_intelligent_traffic_management/Wireless_NetworkReady_Intelligent_Traffic_Management_5.0.0/Wireless_NetworkReady_Intelligent_Traffic_Management/WNR_ITM

# create Network Attachment Definition
kubectl create -f net-sriov-itm.yaml

  2. Apply the network policy using the provided itm_network_policy.yaml file:

    cd wireless_network_ready_intelligent_traffic_management/Wireless_NetworkReady_Intelligent_Traffic_Management_5.0.0/Wireless_NetworkReady_Intelligent_Traffic_Management/WNR_ITM

# create netpol for the ITM
kubectl create -f itm_network_policy.yaml

  3. Deploy Grafana and Influxdb pods using Helm:

    cd WNR_ITM/deploy
Cluster_ControllerIP=$(kubectl get node -o wide |grep control-plane | awk '{print $6}')
helm install grafana ./grafana --set hostIP=${Cluster_ControllerIP}
helm install influxdb ./influxdb

# check the Grafana and Influxdb pod
kubectl get pod -n smartedge-apps

NAME                        READY   STATUS    RESTARTS   AGE
grafana-796b7f677-lsrh4     1/1     Running   0          44h
influxdb-585c4b8bb5-8f2lc   1/1     Running   0          44h

  4. Deploy the ITM application:

    # Get the Grafana sriov ip
grafana_pod=$(kubectl get pod -n smartedge-apps |grep grafana | awk '{print $1}')
sriov_IP=$(kubectl exec -n smartedge-apps ${grafana_pod} -- ip a s net1 | grep inet |awk '{print $2}' | cut -d '/' -f 1)

# helm install ITM
cd WNR_ITM/deploy
grafana_ip=$(kubectl get pod -n smartedge-apps -owide |grep grafana | awk '{print $6}')
Passwd=admin
helm install itm ./itm --set hostIP=${Cluster_ControllerIP} --set sriovIP=${sriov_IP} --set grafanaPassword="${Passwd}" --set grafanaHost=${grafana_ip}

# check the ITM pod
kubectl get pod -n smartedge-apps

NAME                   READY   STATUS    RESTARTS   AGE
itm-75758c684f-cdxt5   1/1     Running   0          44h


    NOTE: <Cluster_ControllerIP> is the cluster controller IP.

  5. Start the nginx service in the Grafana pod by executing the following commands on the controller node.

    kubectl exec -n smartedge-apps ${grafana_pod} -- sudo sed -i "s/try_files \$uri \$uri\/ =404;/proxy_pass http:\/\/${Cluster_ControllerIP}:30300;/"  /etc/nginx/sites-available/default
kubectl exec -n smartedge-apps ${grafana_pod} -- sudo nginx -g "daemon on;"

  6. Add routing rule for Grafana on the edge node:

    # Login to the edge node, and add an additional route rule for Grafana
[smartedge-open@node]# docker ps | grep k8s_grafana_grafana* | awk '{print $1}'
32e0eade6b0d

[smartedge-open@node]# docker inspect -f {{.State.Pid}} 32e0eade6b0d
86372
[smartedge-open@node]# sudo nsenter -n -t 86372

[smartedge-open@node]# sudo ip route add 192.171.1.0/24 via 6.6.6.11

[smartedge-open@node]# route
Kernel IP routing table
Destination     Gateway         Genmask         Flags Metric Ref    Use Iface
default         gateway         0.0.0.0         UG    0      0        0 eth0
6.6.6.0         0.0.0.0         255.255.255.0   U     0      0        0 net1
gateway         0.0.0.0         255.255.255.255 UH    0      0        0 eth0
192.171.1.0     6.6.6.11        255.255.255.0   UG    0      0        0 net1


    NOTE: The subnet 192.171.1.0/24 is the UE (User Equipment) network segment allocated by 5GC network functions.

  7. Add routing rule in the edge node to add an additional rule for edgeDNS.

    Create a net-attach-def resource for edgeDNS:

    $ cat edgedns-net-attch-def.yaml
apiVersion: sriovnetwork.openshift.io/v1
kind: SriovNetwork
metadata:
name: intel-sriov-edgedns
namespace: sriov-network-operator
spec:
resourceName: intel_sriov_10G_VEDIOSTREAM
networkNamespace: smartedge-system
ipam: |-
  {
     "type": "host-local",
     "subnet": "6.6.6.0/24",
     "rangeStart": "6.6.6.66",
     "rangeEnd": "6.6.6.66",
     "routes": [{
        "dst": "0.0.0.0/0"
     }],
     "gateway": "6.6.6.1"
  }

kubectl apply -f edgedns-net-attch-def.yaml

    Patch the original edgedns daemonSet with the following patch:

    $ cat edgedns-ds-patch.yaml
spec:
template:
   metadata:
      annotations:
      k8s.v1.cni.cncf.io/networks: intel-sriov-edgedns
   spec:
      containers:
      - name: edgedns
      resources:
         limits:
            intel.com/intel_sriov_10G_VEDIOSTREAM: "1"
         requests:
            intel.com/intel_sriov_10G_VEDIOSTREAM: "1"

kubectl patch ds -n smartedge-system edgedns --patch "$(cat edgedns-ds-patch.yaml)"

    Login to the edge node, and add an additional route rule for Grafana:

    [smartedge-open@node]# docker ps | grep edgednssvr* | awk '{print $1}'
6e4d8ea23ecb

[smartedge-open@node]# docker inspect -f {{.State.Pid}} 6e4d8ea23ecb
102569
[smartedge-open@node]# sudo nsenter -n -t 102569

[smartedge-open@node]# sudo ip route add 192.171.1.0/24 via 6.6.6.11

[smartedge-open@node]# route
Kernel IP routing table
Destination     Gateway         Genmask         Flags Metric Ref    Use Iface
default         gateway         0.0.0.0         UG    0      0        0 eth0
6.6.6.0         0.0.0.0         255.255.255.0   U     0      0        0 net1
gateway         0.0.0.0         255.255.255.255 UH    0      0        0 eth0
192.171.1.0     6.6.6.11        255.255.255.0   UG    0      0        0 net1

  8. Create a domain name for ITM on the controller node:

    # Replace sriov-ip with real IP, you can get sriov-ip with command 'echo ${sriov_IP}'
kubectl edgedns add www.wnr-itm.com:${sriov_IP}

Step 3: Data Visualization on Grafana

Check the Grafana dashboard in the UE browser.

  1. Input the address "www.wnr-itm.com:3000". Login with user as admin and password as admin. No need to reset password, just skip.

    Click Home --> select one channel to check the ITM data.

  2. Click Home and Select the ITM to open the main dashboard.

     

    Screenshot of Grafana Home Screen
    Figure 5: Grafana Home Screen


     

    Screenshot of Grafana Dashboard List
    Figure 6: Grafana Dashboard List


     




     

    Screenshot of Camera Feed
    Figure 7: Grafana Dashboard of an individual camera feed

     

Step 4: Uninstall the Application

  1. Check installed modules with the following command: 
    cd /home/smartedge-open/wireless_network_ready_intelligent_traffic_management
./edgesoftware list
    All installed modules will be shown as seen in the screen below:
     
    Screenshot of installed modules
    Figure 8: Installed Modules List

     
  2. Run the command below to uninstall all the modules: 
    ./edgesoftware uninstall –a
  1. Run the command below to uninstall the Wireless Network Ready ITM reference implementation: 
    ./edgesoftware uninstall <itm-id get from step 1>

    Screenshot of uninstall success
    Figure 9: Uninstall Modules

     

 

 

Optional Steps

Stop the Application

To remove the deployment of this reference implementation, run the following commands.

NOTE: The following commands will remove all the running pods and the data and configuration stored in the device.

 

helm delete itm

Summary and Next Steps

This application successfully implements Intel® Distribution of OpenVINO™ toolkit plugins for detecting and tracking vehicles and pedestrians and may be used for a basis in estimating a safety metric for an intersection. It can be extended further to provide support for a feed from a network stream (RTSP or camera device).

As a next step, you can experiment with accuracy/throughput trade-offs by substituting object detector models and tracking and collision detection algorithms with alternative ones.

In addition, on an appropriate platform with supporting RAN hardware you can onboard a 3rd party 5G RAN (Radio Access Network) implementation that will make it easy to host a private or public 5G small cell. To perform video analytics wireless IP cameras can be connected through the small cell, and the video traffic from the cameras can be routed via the high-speed SmartEdge-Open data plane to the visual intelligence container. With the 5G RAN and visual intelligence workloads hosted in a single system, the solution benefits from faster data transfers between the workloads and a reduced total cost of ownership.

Learn More

To continue your learning, see the following guides and software resources:

Troubleshooting

Pods status check

Verify that the pods are Ready as well as in Running state using below command:

kubectl get pods -n smartedge-apps

If any pods are not in Running state, use the following command to get more information about the pod state:

kubectl describe -n smartedge-apps pod <pod_name>

Pod status shows “ContainerCreating” for long time

If Pod status shows “ContainerCreating” or “Error” or “CrashLoopBackOff” for a while (5 minutes or more), run the following commands:

reboot
su
swapoff -a
systemctl restart kubelet  # Wait till all pods are in “Running” state.
./edgesoftware install

Subprocess:32 issue

If you see any error related to subprocess, run the command below:

pip install --ignore-installed subprocess32==3.5.4

Grafana Dashboard Not Showing on Browser

Run the following commands:

# check the itm pod log
kubectl logs <itm-pod-name> -n smartedge-apps

Support Forum

If you're unable to resolve your issues, contact the Support Forum.

To attach the installation logs with your issue, execute the command below to consolidate a list of the log files in tar.gz compressed format, e.g., ITM.tar.gz.

tar -czvf ITM.tar.gz /var/log/esb-cli/Wireless_NetworkReady_Intelligent_Traffic_Management_<version>/<Component_name>/install.log

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.