Commercial Drone Operations: Automating the Manual Workflows

Commercial drone operations

Across every industry, commercial drone operations are creating new opportunities for enterprises, SMBs, and nonprofits to innovate their business models. Drones are optimizing last-mile deliveries, transporting urgent medical supplies, inspecting oil pipelines, and improving search and rescue efforts. In many cases, drone technology has proven to be a more efficient, cost-effective solution, filling the gaps where traditional ways of doing business have fallen short.

It’s fair to say there are many benefits to launching a commercial drone operation, but where do you begin? The process can feel daunting, and understandably so. Businesses have several responsibilities to ensure their operation is safe, secure, and compliant. To name a few…

  • Regulatory compliance: Commercial operators in the U.S. are required to obtain a remote pilot certificate, register their drones, and receive airspace authorization. During flight, they’re also expected to comply with Part 107 regulations unless a waiver has been approved for more advanced operations, such as flying beyond visual line of sight, at night, or over people.
  • Flight operations: Commercial operators are expected to plan and execute their flights and share operational data with the UAS traffic management (UTM) ecosystem. Accurate, up-to-date flight plans are required to optimize the airspace and avoid unnecessary deconfliction.
  • Aircraft deconfliction: Operators are responsible for staying on top of changes in the airspace and adapting their flights accordingly. This requires operators to monitor airspace traffic, regulatory dynamics, and local conditions, such as weather, terrain, buildings, and risks on the ground.
  • Aircraft security: Businesses are responsible for protecting their commercial drone operation from both intentional acts (e.g., cyberthreats) and unintentional acts (e.g., human error, hardware malfunction), affecting people or property in the air or on the ground. This requires operators to continuously monitor their aircraft performance and detect any malicious activity.
  • Contingency management: In the event of a contingency, operators are responsible for notifying authorities and affected operators of the new flight plan and emergency status until the hazard is no longer a risk. Contingencies include an active flight that is undergoing a critical equipment failure, experiencing a loss of tracking capabilities, or operating outside the bounds of their intended flight path. In case an incident occurs, commercial drone operators also need to maintain high standards of auditability by recording all flight and service logs.

What if these responsibilities weren’t so daunting? What if there was a way to simplify how businesses plan, execute, and manage their commercial drone operation?

Fortunately, technology advancements in AI and blockchain are making it possible to eliminate the manual workflows and enable safe, autonomous operations. For example, when it comes to flight operations, AI technology can analyze crucial data, such as airspace traffic, weather forecasts, ground risks, and aircraft performance, to automatically generate optimal flight paths and autonomously adapt flights as conditions change.

When it comes to regulatory compliance, blockchain can encode the airspace rules, such as flying below 400 feet during daylight hours, as mandatory parameters in a flight planning system. Businesses can also use this technology to set company-wide safety standards for their commercial drone operations, such as flying with at least 20% battery life in reserve. The approach helps automate compliance and ensures all drone operators associated with your organization are following the same rulebook.

Check out our latest eBook to learn more about automating the manual workflows. This comprehensive guide will help prepare your organization for a safe, efficient, and scalable commercial drone operation.
 

Urban Air Mobility in 2020: Four Trends to Watch

Urban air mobility

From autonomous aerial taxis to cargo vehicles, hardware advancements in the urban air mobility market are underway. Regulatory standards and software platforms are also beginning to take shape. In fact, the FAA estimates 545,000 commercial drones will be in use by the end of 2020. These drones will be performing real commercial tasks – they’ll deliver packages, transport people, conduct industrial inspections and provide emergency assistance.

As more unmanned aircraft begin operating, there are four key technologies that will help ensure the safety and security of our airspace.

Drone Security: Preventing Malicious Activity with AI-Powered Cybersecurity

In the near future, there will be a network of flying computers in the sky. Just like the computer servers we use today, these drones could be hacked if not secured properly, posing dangers when they’re flying above a crowd of people or a busy highway.

And in this emerging environment, new security threats could also take the form of previously unseen, “zero-day” attacks. Traditional anti-malware software, dependent on signatures of known threats, won’t be adequate to detect this unknown malware.

AI-powered cybersecurity will be the key to detecting malicious activity on the edge and preventing it from making its way on to a drone or executing on it. An AI-based approach can learn the DNA of what a malicious file might look like instead of merely relying on an existing threat database. This type of technology can function even when network connectivity is non-existent or impaired and can defend drones against zero-day threats. AI-powered cybersecurity will be key in ensuring public safety by providing an adaptable system that protects against never-before-seen attacks.

Drone Data Integrity: Protecting Vehicle and Flight Data with Distributed Ledger Technologies (DLT)

The use of distributed data storage technologies that implement consensus and trust will also be essential to the urban air mobility market. A distributed ledger of immutable transactions can ensure drone data and flight logs are stored securely and accurately.

DLT, augmented with AI-powered “smart contracts”, which execute safely and under guarantees of performance, can create a verified data source airspace authorities can rely on when auditing drone operations or analyzing an incident. DLTs augmented into a future “Aviation OS” will allow flight logs to be stored securely and privately in real time. Since data can be offboarded from the aircraft rapidly and can’t be overwritten, authorities can determine a sequence of events with 100% certainty. Storing transactions on a shared digital ledger also eliminates the need for paper records and opens the opportunity for collaboration that hasn’t existed in the past. There are still many paper records and documents used in manned aviation that simply can’t be relied upon as we make the transition to a world with millions of autonomous aircraft in the sky.

From an operator’s perspective, digital ledgers can also help ensure all safety standards are being met. For example, if a business wants all drones to receive a system check after 100 hours of flight, they can encode this as a rule implemented by a smart contract that must be resolved with a private key before the drone can fly again.

Drone Maintenance: Managing Maintenance Requests with Predictive AI Analytics

Once businesses begin to scale their drone operations, it will no longer remain realistic for humans to safely monitor and track their performance. Predictive AI analytics will monitor the performance and behavior of drone fleets and return actionable insights. These insights can flag suboptimal operations and forecast vehicle health.

For example, predictive models might determine that a specific drone’s battery, under specific weather and usage patterns, is likely to degrade after flying for 200 hours. When a drone is close to hitting 200 hours, AI can be used to automatically generate a maintenance request for a battery replacement and assign the request to a technician upon landing at a facility. DTL can also ensure the maintenance request is resolved and signed off by a technician’s private key before the drone can operate again.

This approach to predictive maintenance can help alleviate the burden on humans and ensure drones are always safe to fly.

Drone Deconfliction: Avoiding In-flight Hazards with Intelligent Deconfliction 

One of the biggest concerns when it comes to large-scale drone deployments is around how these drones will “sense and avoid” other aircraft and potential hazards in the airspace. Reliable “sense and avoid” is crucial to safely enable operations that go beyond visual line of sight. For example, another drone may suddenly enter a drone’s flight path, the wind may pick up unexpectedly or the FAA may issue a notice to airmen (NOTAM) that restricts the current route.

Intelligent deconfliction technology can help solve this challenge by constantly updating a drone’s route to account for new hazards and changes in operating conditions. As with drone maintenance needs, humans alone cannot be relied upon to avoid unexpected obstacles in the airspace.

Artificial intelligence will be necessary to safely sense and avoid new obstacles in-flight, or completely reroute the drone if the new conditions are extreme. This technology must also account for other aircraft to ensure there are no conflicting routes.

Ultimately, the possibilities enabled by urban air mobility will be transformative for industry and society in the not-too-distant future. But first, we must have the right technologies in place to ensure that every flight is a safe flight!

By Amir Husain, CEO & founder of SkyGrid. This article was originally published in Forbes.