Inspiration

Managing safety in cities and towns require agility, efficiency and team play. MissionMonitor supports public safety providers with an app-based solution to manage equipments, operations, and teams at highest precision.

In public safety work where every second counts, it is important to receive intelligence from various sources in real time so that safety, security and mission success are not impacted. Also, it is important to monitor the health of officers as well as equipments like drones, cameras, and fleet of vehicles.

What it does

The solution uses 5G, Multi-access edge computing (MEC), Machine Learning, Wearable, Robotics, Drones, and Internet of Things. It can be learned quickly and be operational within minutes from any mobile phone, tablet or web browser on your desktop.

Officers, cameras, and other devices in the field can quickly log incidents using AI, wearable, mobile and IoT apps, so that all incidents are tracked in the MissionMonitor operations center and open notifications and alerts can be seen at a glance.

Position of officers and places of interests can be tracked on the map. This helps with situational awareness and for incidents to be dealt with quickly.

Cameras running computer vision algorithms are used to detect, analyze, and alert public safety to emergencies from streaming data where every second counts. The streaming data from the camera include video and still images from the following examples: IoT cameras, vehicle cameras, robot, and drone. AI processing applications deployed on an EC2 instance in the AWS Wavelength Dallas zone perform computation on the data stream. An API server receiving data from various source performs the fusion of data including those from the edge device cameras, IoT and mobile devices. Early detection using AI technology that works with cameras on the edge will help the public.

A wearable and mobile solution allows the continuous monitoring of health vitals for first responders. The solution includes an Android app for real-time activity is connected to MissionMonitor web and online dashboard for danger and health data visualization.

Examples of emergency events constantly tracked include: fall, heart rate, automated license plate reading, brandishing a gun and active shooter.

A drone deliver live aerial video streams to MissionMonitor dashboard for scene intelligence and guidance during mission-critical and lifesaving public safety operations. Video feeds provide accurate and real-time geographical information for saving lives in danger.

In a situation where first responders face the unknown, a robot can remove uncertainty by going into the unknown areas and stream video feeds.

How we built it

Android Java and Tizen web apps on a samsung wearable are used to monitor officer health. Apache Kafka, OBD-II, Verizon Mobile WiFi, cameras, and tiny computers like raspberry Pis are used for fleet management, as well as monitoring the interior and exterior of each public safety employee's vehicle. This involves using python for streaming IoT data and video frames to endpoints including the ones serving tensorflow. The MissionMonitor dashboard is built with Vue with connections to a backend NodeJS server and other backend flask servers serving tensorflow models. Some cameras are connected to raspberry pi and Monarch Go Pi HAT for cellular connectivity.

Accomplishments that we're proud of

Building from idea to a working prototype.

What we learned

I learnt a lot about AWS Wavelength, and other technologies used to build the solution

What's next for MissionMonitor

I am planning to integrate the solution with augmented reality to deliver feeds from various sources including data from wearables, cameras and drones to the eyes of officers.

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