Drone Delivery Platform with Advanced Route Management
Key results
- Autonomous drone operations
- Centralized drone fleet management platform
About the Client
Our client is building the world’s first drone-based delivery service – cutting delivery costs and times by order of magnitude in an (almost) infinite market. In 2017 they launched the world’s first fully operational, regulatory-approved, on-demand drone delivery service in Reykjavik, Iceland, and became the leading competitor in the race to deploy a true on-demand delivery service via autonomous vehicles.
While the majority of packages that require transit across cities are no heavier than 2lbs, client’s drones are able to carry up to 6.5lbs and travel a distance of approximately 6 aerial miles. The drones require minimal handling, thus reducing manpower and ensuring a quick delivery every time.
Business Challenge
The client had a truly revolutionary idea: to make drone delivery simpler, faster, and, of course, cheaper. Yes, using drones for delivery is nothing new, but all those drones are remotely controlled by a pilot. So, our client wanted to develop the world’s first drones handled over the cloud from the Control Center. This would help operate a fleet of drones automatically, safely, and cost-effectively without a pilot.
Solution Overview
Our team created an advanced yet easy-to-use online dashboard that combines all the tools you need to manage your fleet of delivery drones. The dashboard is beneficial whether your fleet includes a single drone making deliveries within an exclusive resort or tens of drones delivering consumer goods across an entire city.
Following the EU Aviation Safety Agency’s measures, some situations, like extreme weather conditions, service, and connection loss, raise questions about a different solution for an emergency landing to return drones to the start point to prevent accidents.
Implementation
When the client addressed us, he already had the project’s first version. Our job was to develop the second production-ready version that let us focus on the features and architecture upgrade.
Our team developed the four main features:
- Advanced Route Management
Users can define flight routes with unlimited smart way-points. Drones can take off and land from a single center or multiple centers.
- Smart Way-Points
Users use actionable way-points to define different actions across routes; land with or without recipient approval, wire release from mid-air, fly between trees, and other obstacles.
- Reports
Provides users with detailed reports for each mission, including complete telemetry data, flight playback, server logs, and flight controller reporting.
- Automatic Preflight Check
The system automatically performs a full system preflight check before approving each takeoff, verifying hardware readiness, flight route availability, and weather conditions.
Architecture restructuring
The main challenge was splitting the solution’s monolithic architecture into four microservices. The system’s connections and transactions also had to be very fast since the solution had to work in real time. On top of that, the system had to keep working even during critical moments like service crashes or lost connections. We rebuilt the infrastructure, and now the system has scenarios for different situations.
Building an architecture with separate stateless services was an excellent decision regarding fault tolerance. Each of the four components can work as a single service, meaning that if one or even several services break down, the system will still work. A service hanging for some time will try to reconnect to the system automatically once it is restored. That ensures the uninterrupted operation of all drones.
Technological Details
The back-end part was developed using Python (a Django framework) and Postgres (a relational database). The service contains four components connected via WebSockets and uses Redis for communication between servers or task processing. The system works using Docker and is deployed on the AWS infrastructure.
KPIs
4
core management features for routes, waypoints, and reporting100%
automated preflight checks for enhanced safety
Location
- Iceland
Industry
- Logistics
Services
- AI & Machine Learning
- IoT & Embedded Systems
Technologies
- Python
- Django
- Redis
- Docker
- Postgres