Revolutionizing Agriculture with Drones

Revolutionizing Agriculture with Drones with SkyGrid

The integration of technology with everyday operations has become commonplace across industries and sectors. Particularly, the drone industry has seen a steady and impressive rise in its implementation in various industries. One sector that has significantly benefited from the use of drones is agriculture. 

Advancements in drone technology have led to the development of much more efficient and varied agriculture strategies. As a result, farmers are able to enjoy their work differently through innovative technologies such as artificial intelligence and automation systems. Operations such as surveillance, monitoring, and maintenance that are labor-intensive and time-consuming offer ideal conditions for drones to flourish. Precision farming can be achieved by drones faster and more accurately as well. Irrigation, field analysis, crop mapping, and monitoring are some of the tasks that have begun to rely on drone technology. 

 

Implementation of High-Tech Drones 

A combination of integrated hardware components and the latest software models are used to create technology such as drone sensors and cameras that have helped create the concept of smart farming. Smart farming has provided a sustainable and clean model of food production. 

Some of the more notable technologies that have improved drone technology, improving agricultural processes, in turn, are artificial intelligence, sensors, drone camera, and GPS. The resulting products help with monitoring, tracking, and inspection of farms. 

One example of how smart farming is more efficient than conventional farming is the capturing of data. Sensors are installed in drones that can record information about light, temperature, humidity, and soil conditions. 

 

Precision Farming 

 A 2019 definition by the International Society of Precision Agriculture defines precision agriculture as “a management strategy that gathers, processes and analyzes temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production.” 

Precision agriculture presents quality solutions for smart farming. Some of the major technologies that make up precision farming are: 

  • Automation systems 
  • Multispectral sensors 
  • Robotics 
  • Variable rate technology 
  • Fourth and fifth-generation mobile data transmission 
  • Global Positioning System (GPS) 

 

Monitoring Fields 

There are several factors and elements that need to be constantly and reliably monitored. A combination of ground-based drones and aerial-based drones has proven to be effective monitoring methods. Drone cameras are able to capture accurate information that can also be used to monitor progress and performance over a period of time. The implementation of drones for monitoring aids with tasks such as: 

  • Crop health assessments 
  • Crop monitoring 
  • Planting 
  • Field assessments 
  • Irrigation 

Additionally, factors such as wind speed, sunlight, moisture levels, and depth that need to be tracked can be done so much more easily using multispectral sensors that are present in drones. 

Efficient monitoring systems are extended to livestock farming as well. Large farms are more smoothly managed with the modern technologies drones are equipped with. The health and location of livestock can be monitored and recorded. This reduces the risks of loss due to diseases and other calamities that can often befall cattle. For instance, diseases can be picked up quickly, and affected cattle can be immediately separated to prevent further spreading. 

An added benefit of using automated monitoring systems for smart farming instead of relying on manual labor is the saved labor costs. 

According to the Agriculture Drone Market report by Reports and Insights, the global agriculture drone market in 2020 was estimated to be more than $1.3 billion. It’s expected to reach $10.5 billion by 2028, with a significant CAGR of 35.6%. The technological revolution is a necessary one for the agriculture sector. Amidst strained food production across the world and the problems posed by climate change, implementing intelligent technologies to combat these problems and devise more effective strategies to stay afloat is crucial. The drone industry provides these solutions for the agriculture sector on a major level. 

Skygrid has worked to provide solutions to the problems faced across numerous industries, including agriculture. To learn more about how we integrate the latest technologies into creating innovative drone technology, visit our website!

Automation, AI & Blockchain: The keys to unlock BVLOS

Automation, AI & Blockchain

As drone technology becomes increasingly automated, the level of human involvement is shifting from remote pilots in the field to remote operators in the office. This approach can enable more scalability and operational oversight as enterprises grow their drone fleets to inspect pipelines, monitor crops, or survey infrastructure. However, several barriers still exist when it comes to safely enabling Beyond Visual Line of Sight (BVLOS) operations. 

Let’s explore some of the things that are required to unlock BVLOS operations, including remote automation, safety & compliance rule enforcement, AI-powered cybersecurity, and more. 

Drones are disrupting various industries and innovating outdated business models. BVLOS enables UAVs to operate beyond the normal vision range of the pilot. BVLOS capabilities are becoming a quintessential aspect of the drone industry. They provide numerous benefits over the regular line of sight flights. They are cost-effective, energy-efficient with fewer takeoffs and landing phases, cover significant ground in a single flight, and drones’ low-altitude flying capability can help in high-resolution data collection.  

In many cases, businesses need to operate drones beyond visual line of sight to complete a wide range of missions, such as assessing hurricane damage and delivering aid to the devastated areas or inspecting pipelines to prevent leaks in the oil and gas industry. That means they’ll need more advanced technology in place to identify other aircraft, stay up to date on airspace changes, and safely reroute drones to avoid potential hazards. Let’s first consider the challenges commercial drone operators are facing today. 

Airspace management   

We all know there are many benefits to launching a drone operation, but navigating low-altitude airspace is complex. The burden has fallen on drone operators to manually evaluate the airspace, plan their flight paths, and avoid hazards as conditions change. But this approach isn’t scalable when you consider the volume of data operators are expected to evaluate for a successful mission. 

Today’s systems require too many manual workflows that limit scalability and leave room for error in the rapidly changing airspace. Drone operators are expected to monitor weather changes, avoid buildings and construction cranes, factor in risks on the ground, and comply with shifting regulatory dynamics. The burden typically falls on them to manually plan, execute, and adapt their flights as these conditions change.   

At the same, drone operators are challenged by disconnected systems. They typically have to use several different tools to check airspace conditions, plan and execute missions, and gather insights. But it’s a cumbersome process that leads to disconnected information as operators switch between different applications. 

  • Traffic: For starters, operators need to check airspace traffic, including both manned and unmanned traffic, to maintain safe separation. To minimize public safety risks, operators also need to evaluate activity on the ground below, such as roadway and foot traffic. 
  • Regulations: From a regulatory standpoint, they also need to check airspace classes and boundaries and monitor shifting dynamics, such as temporary flight restrictions and notices to airmen.  
  • Weather: Access to micro-weather data is also important to check precipitation, wind, temperature, and visibility. These factors can impact the flight path, battery life, and overall success of the mission.  
  • Infrastructure: Drone operators also need to evaluate local buildings, bridges, schools, stadiums, and airports to navigate around densely populated areas.   
  • Environment: They also must also check the local elevation and terrain to avoid potential hazards.   
Security and safety  

Those are just the external factors operators are expected to evaluate. Operators also have to consider the health and security of their aircraft. They’re ultimately responsible for protecting their drones from both intentional acts, such as cyber threats, and unintentional acts, such as hardware malfunction.  

  • Aircraft health: This requires operators to continuously monitor their vehicle health, but that becomes a lot more challenging as a fleet grows.  
  • Aircraft security: From a security perspective, operators also are expected to protect their drones from malicious activity. Just like the computers we use today, drones can be hacked if not appropriately secured, posing dangers to people and property on the ground.  
Automation, AI & Blockchain 

The bottom line is it’s not feasible to manually monitor and interpret this exceptional volume of data at scale. A new approach is required to simplify drone operations with a connected system that automates every phase of flight, removes the burden on drone operators, and allows operators to focus on overseeing the mission’s success. This is where advanced technologies like artificial intelligence and blockchain can help.  

AI algorithms are trained to analyze a large volume, variety, and velocity of data and instantly act on the insights. These algorithms automatically learn from patterns to uncover and act on trends hidden from the human eye. 

In technical terms, blockchain is a distributed ledger of immutable records stored in a decentralized database. In layman’s terms, it enables safe and accurate record-keeping across a network of computers, allowing multiple parties to interact with the same universal source of truth using a private key. “Smart contracts” are also a key component of blockchain technology. Smart contracts can be encoded on any blockchain to set rules mutually agreed upon by network members and automatically execute the terms without human intervention.  

When used in parallel, these advanced technologies can help eliminate manual workflows and enable safe BVLOS operations. Let’s walk you through a few examples.  

Automated flights:  

AI algorithms can be trained to calculate the optimal route for one or more drones based on the mission parameters, such as the start and endpoint, desired cruise altitude, timeframe, and payload details. These algorithms can also factor in airspace, vehicle, and location data, such as weather, terrain, population density, and roadway traffic, to generate routes that minimize risks in the air and on the ground.  

During the flight, the AI models will monitor, predict, and adapt to conditions as they change. This approach essentially removes the burden on commercial operators by enabling autonomous workflows that are safe and scalable as a fleet grows.  

Mandated compliance:  

When it comes to regulatory compliance, blockchain augmented with smart contracts can encode the airspace rules, such as flying below 400 feet during daylight hours, as mandatory parameters in a flight planning system. Organizations can also use this technology to set additional company-wide safety standards for their commercial drone operations, such as flying with at least 20% battery life under 25 mph winds.  

The blockchain smart contracts automatically record information onto the ledger and execute the terms without human intervention. This approach helps automate compliance with the rules before flight authorization and during flight as airspace conditions change. It also helps ensure all drone operators associated with your organization are following the same rulebook. 

Predictive maintenance 

When it comes to monitoring your vehicle health, predictive AI technology can remove the burden on operators by analyzing sensor data across your fleet and flagging suboptimal operations. An AI-based approach can more accurately monitor performance to forecast vehicle health and identify impending failures before they occur.  

If a potential issue is identified, such as a degrading battery, AI technology can automatically generate a maintenance request and assign the request to a technician upon landing at a facility. Blockchain technology, augmented with smart contracts, can also ensure the maintenance request is resolved and signed off by a technician’s private key before the drone can operate again. 

AI-powered cybersecurity 

In the emerging UAV environment, new security threats will often 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 critical to detect malicious activity on the edge and prevent it from executing on a drone.  

An AI-based approach can learn the DNA of what a malicious file might look like instead of relying on an existing threat database. This approach protects drones from never-before-seen attacks and can still function when network connectivity is non-existent or impaired. 

Systems today are largely disconnected and still rely on humans to manually plan their flights, comply with regulations, and adapt to changing conditions. Advanced technologies like AI and blockchain can enable a new, automated approach. This approach still relies on human input, but it allows more scalability by automatically planning, executing, and adapting flights as conditions change. It also enables enterprises to scale their drone operations by ensuring all pilots associated with their organization remain compliant with the regulations, business rules, and safety standards.

To learn how SkyGrid’s AerialOS can help improve your BVLOS operations, check out our overview page here or learn more about our advanced enterprise features.

 

Why Drone Programs Need to Integrate with New Technologies to Deliver Value

Ways Drone Programs Can Integrate With Other Robotics to Deliver Value

The use of drones in the commercial sector has skyrocketed in the last few years, and their potential is still yet to be fully seen. In 2016, the FAA defined the procedures for commercial drone use, and since then companies have increasingly turned to the new technology to support a number of business-facing priorities.

How drones are expected to impact multiple industries

The drone market size is expected to grow to a massive $63.6B by 2025, with much of that growth being driven by enterprise adoption in the agriculture, construction and mining, insurance, media and telecommunications, and law enforcement industries.

Because drones are able to get to hard to reach locations, they make perfect devices to assess the damage after a disaster, properly assess a construction site, and analyze farm fields to ensure crop output. Drones are also expected to make a huge impact on warehouse operations, improving overall inventory management, providing logistical support, and inspecting conditions that can help maintain a warehouse’s longevity.

Drones are also expected to be a major contributor to last-mile delivery, leading to deeper discounts companies can use to pass on to their customers and increase their market share.

But how organizations integrate and incorporate drones as part of their business development plans will be key in ensuring the technology makes a transformational impact. Several executive leaders have identified drone fleet management, airspace management, universal traffic management, as well as logistics, and operational management as crucial factors that need to be considered for drones to be used to their maximum potential.

How management solutions can address current challenges in drone management

Without the right drone management and airspace management system in place, your drone fleet program launch may lack key efficiencies that will eat away at the benefits you may have forecasted. 

Airspace visibility

Airspace visibility is crucial to ensure your drones have clear flight paths on their missions even in the face of external changes. Having a solution that accounts for changes in conditions and details is necessary in order to maintain operational efficiency and to keep your drones intact. 

A universal traffic management solution should be able to detect and alert you to any local environment conditions, any obstacles that may suddenly appear, and changes in weather conditions like temperature, wind, and precipitation. Without the right visibility, you’re essentially flying blind.

Maintenance gaps

Not being able to forecast maintenance requirements and overall drone performance can hinder a mission’s effectiveness and the longevity of your drone fleet. Having a platform that can not only predict when a drone will require a calibration adjustment or motor cleaning but also streamlines the process via measurable work orders centralizes the process, helping your team save time while increasing your drone’s longevity.

This can have significant long-term impacts on the effectiveness of your drone fleet, while minimizing any costs required in overall maintenance and drone device replacements.

Automating processes

Manual workflows can slow your team down as they try to obtain mission authorizations, certifications, and approvals, meet flight requirements, and ensure they’re adhering to any compliance or regulations. However, automated solutions can lessen the burden and automate many of the authorization requests, freeing up your team to handle more important and pressing tasks.

Leveraging key technologies for improving drone integration and performance

The use of AI has dramatically impacted how solutions handle drone management and airspace management. AI is, arguably, required, in order to handle and analyze the huge amounts of data that is constantly changing on a real-time basis. Otherwise, you may not be able to properly account for your airspace conditions or adapt your flight details in real-time. AI can give your team better information, faster, improving mission effectiveness.

New advances in blockchain technology and fostering the development of smart contracts can improve the certification and authorization process while helping drones meet flight requirements and specifications in certain airspaces. Blockchain technology can also be used to improve overall drone management, helping log flights and maintenance records in a more secure and accurate manner.

As organizations look to incorporate drones, they should take the time to ensure they have the right infrastructure and platforms to help support them.

To learn how SkyGrid’s AerialOS can help improve your airspace management, check out our overview page here



Advancing the Use of AI and Blockchain Technology for Air Traffic Management

SkyGrid Advancing the Use of AI and Blockchain Technology for Air Traffic Management

Today, unmanned aerial vehicles (UAVs) are making their mark in various industries, especially in government and defense operations. The global military drone market is progressing at an unprecedented pace, and the technology and its application to military operations continue to expand across the world. The growing global military UAV market is projected to reach $26.12 billion in 2028 at a CAGR of 12.78%. The considerable increase in UAVs used for defense, EMS, fire, and law enforcement demands a groundbreaking approach to operate these autonomous vehicles safely and efficiently in first responder scenarios such as search and rescue missions, heavy lift cargo, fire response, and medical evacuation. 

New technologies have real potential to assist first responders. For instance, UAVs could make response faster, more targeted, keep responders safer, and provide opportunities for missions impossible for manned aircraft. However, these UAVs also require unique air traffic management solutions, advanced communications to keep everyone aware of what’s happening on the ground and in the sky, and onboarding tools to let them operate safely. 

Working to tackle these challenges  

SkyGrid, in partnership with SparkCognition Government Systems (SGS) and LIFT Aircraft, has been awarded a contract from the Air Force Research Laboratory (AFRL) through its SBIR Phase II program to advance the use of artificial intelligence (AI) and blockchain technology for air traffic management. 

Together, our companies will help enable the U.S. Air Force (USAF) to safely and efficiently operate unmanned aerial vehicles in first responder scenarios by applying AI and blockchain technology to manage the airspace for autonomous vehicles, specifically HEXA, LIFT’s electric vertical take-off and landing (eVTOL) aircraft. 

AI-powered platform to optimize air traffic management 

Artificial intelligence is a key driver in revolutionizing air traffic management systems. Built on AI, the SkyGrid platform takes a smarter approach to aerial mobility.    

For example, SkyGrid’s AI algorithms analyze crucial data, such as airspace traffic, local conditions, ground risks, flight restrictions, and weather forecasts to avoid hazardous conditions. Equipped with AI, in-flight monitoring to ensure safe operations and optimal paths is possible. Our system also monitors drone flights in real-time and notifies operators of anomalies, automatically generating new routes to avoid obstacles or restricted airspace. 

AI-powered air traffic management enables intelligent deconfliction of flights based on real-world variables by sensing and avoiding other aircraft and objects with pre-flight and in-flight deconfliction capabilities. Continuous fleet health monitoring and predictive maintenance optimize drone fleets and reduce time to service with fleet performance recommendations. Our AI-based system automatically generates maintenance tickets and assigns them to technicians upon landing at a facility and tracks all drones, flight logs, and service records in a single dashboard.   

Blockchain-based airspace management to ensure immutable data reporting  

Blockchain technology helps eliminate the potential for human error in the airspace. Augmented with smart contracts, blockchain is the key to ensuring unmanned flights comply with the airspace rules and regulations.  

An airspace system built on blockchain technology makes it easy for operators to share accurate flight plans in real-time and maintain high standards of auditability. Our blockchain-backed system assigns a unique ID to every drone and maintains a real-time record of each drone’s status, flight details (e.g., altitude, location, operator), and maintenance history, as historical flight logs are also crucial to ensure the security and integrity of data exchanged between operators, authorities, and service suppliers. Each flight log is linked to the previous record with cryptography, so they can’t be altered retroactively.  

The decentralized nature of a blockchain system also provides more security than traditional, centralized storage since there’s not one database a bad actor can compromise. This approach enables authorities to analyze flight data and determine a sequence of events with certainty. It gives organizations a secure, accurate record of their flights to evaluate performance and optimize operations.  

Leading the way to advance air traffic management 

By combining SGS’s advanced AI technologies, SkyGrid’s AI and blockchain-based airspace management capabilities, and LIFT’s state-of-the-art UAVs, our companies will develop an air traffic management solution that provides defense, EMS, fire, and law enforcement with the means to advance their missions and more quickly respond to emergency situations. 

A Holistic Approach to UAV Safety

SkyGrid Flight Control: A Holistic Approach to UAV Safety

The Federal Aviation Administration (FAA) predicts the future of commercial UAS fleet by 2025. 

From autonomous drones to air taxis, the urban air mobility market has advanced rapidly over the last two to three years. These drones are performing real commercial tasks – they are delivering packages, conducting industrial inspections, providing emergency assistance, and will eventually transport people.  

Based on the latest data, the Federal Aviation Administration (FAA) predicts the commercial UAS fleet by 2025 will likely number 835,000 vehicles. 1.7 times larger than the current number of commercial sUAS. More drones are expected to take flight in coming years spanning a wide range of civilian and commercial use cases, but all this comes with as-yet unaddressed challenges. Drone data integrity, maintenance, and drone deconfliction need to be addressed. These issues range in severity from inconvenient to dangerous. On the one hand, significant growth in drone numbers and capability is incredibly exciting, however, this also presents a major challenge in terms of effectively protecting aircraft systems from being attacked by zero-day cybersecurity threats remotely. 

SkyGrid: A Holistic Approach to UAV Safety
Preventing Malicious Activity with AI-Powered Cybersecurity

With the rise of communication between people and devices and the rise of computing performance, aircraft such as drones are not immune to cybersecurity risks that have become prevalent and critical issues for other industries. Large numbers of airborne drones are essentially a network of flying computers in the sky. Just like the computers we use today, these drones can be hacked if not secured properly, posing dangers when they are flying close to a crowd of people or a busy highway. 

In this emerging environment, new security threats will often take the form of previously unseen, “zero-day” attacks. Traditional anti-malware software, dependent on signatures of known threats, will not be adequate to detect such sophisticated, new malware.  

AI-powered cybersecurity holds the key to detecting malicious activity on the edge and preventing it from making its way on to a drone or executing on its computer systems. An AI-based approach can learn the DNA – the structure – 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.  

Leveraging machine learning technology combined with a “defense in depth” approach can provide multiple layers of protection for an endpoint. Cognitive cybersecurity solutions enable more advanced airspace security than traditional anti- malware systems which remain reliant on signatures of known threats. In contrast to known signatures, heuristics, or other dated rules-based approaches to detect security threats, the DeepArmor® product uses patented machine learning technology and a layered protection strategy to protect a drone’s endpoints. Not only can DeepArmor® protect drones from known threats, its machine-learning detection engine also uses advanced classification algorithms to predict and prevent zero-day attacks, enhancing protection. 

SkyGrid A Holistic Approach to UAV Safety
A new era of protection for drones in defense

DeepArmor® is already proven and effective in the commercial sector. Now, the technology can be extended for use on UAVs within the defense industry to counter national security threats. Considering emerging threats as seen in the capture of the RQ- 170 by Iran are now a fact of life, an AI-based approach is critical to detect and prevent such cyberattacks. The DeepArmor® Aerial product can provide this detection and protection by deploying directly on drone hardware even when network connectivity is impaired or non-existent. 

Boeing and SparkCognition’s joint venture, SkyGrid, is taking this new, intelligent approach to security by employing AI to detect and prevent cyberattacks from impacting a drone, a payload, or a ground station. Integrated with SkyGrid’s airspace management system, AerialOS™, the DeepArmor® product can be deployed directly on drone hardware to extend AI protection and defend drones from sophisticated cyber-attacks. 

By Zehra Akbar, VP, Strategy & Operations of SkyGrid. This article was originally published in Cognitive Times Vol.17. 

Download SkyGrid Flight Control for free in the iPad App Store or learn more about our advanced enterprise features. 

AI Meets Drones: Detecting Objects In-Flight with Computer Vision

drone computer vision

Over the last two to three years, artificial intelligence has been a game changer for the drone industry. AI can be used to autonomously execute safe flight plans, predict drone maintenance needs, and protect drones from cybersecurity attacks.

During flight, AI can also be used to detect and track objects of interest in real-time through computer vision. This powerful technology is opening the door to new drone use cases that were previously unimaginable. It can help improve emergency response, animal conservation, perimeter security, site inspections, and much more.

Our free SkyGrid Flight Control app is equipped with computer vision to detect people, vehicles, animals, and other key objects in real-time as drone operators autonomously surveil a defined area. Get the scoop below and read on for more details.


 

What is computer vision?

Computer vision is a field of artificial intelligence that trains computers to identify, interpret, and track objects in imagery and video. The technology is driven by pattern recognition. It’s trained by feeding computer models thousands to millions of images with labeled objects. This allows the algorithms to establish a profile (e.g., color, shape) for each object to then identify the objects in unlabeled images.

Thanks to advances in machine learning and neural networks, computer vision has made great leaps in recent years and can often surpass the human eye in detecting and labeling certain objects. One of the driving factors behind this growth is the amount of data we generate that can be used to train computer vision models more accurately.
 

How does SkyGrid’s computer vision work?

Our computer vision is powered by a well-known neural network called YOLO, short for You Only Look Once. The YOLO object detection model is especially popular for real-time on-device systems because it is both small and very fast, while still maintaining high levels of accuracy. The models have been trained to recognize 80 different categories of common objects, such as people, cars, trucks, animals, electronics, and other objects. As a result, the SkyGrid Flight Control app achieves near real-time object detection (about 10-20 frames per second on an iPad) through a drone’s live video stream. See example below.

drone computer vision

SkyGrid Flight Control also enables users to select a detected object and track it through a drone’s live video feed. The algorithm itself is very performant, running at 60+ frames per second on an iPad.

drone object detection

Why kind of use cases can drone computer vision enable?

Our computer vision capabilities can support a wide variety of recreational and commercial drone use cases. It can help identify a missing person during a search and rescue operation or detect potential threats near critical infrastructure, such as an oil pipeline or high-security building. It can be used to count cars in parking lots to predict retail earnings or used to monitor wildlife to detect potential poachers. It can even help monitor social distancing to prevent the spread of COVID-19.

For enterprise customers, SkyGrid can train models to detect and track custom objects based on the mission objectives. For example, models could be trained to detect hurricane debris to help identify the most damaged areas in need of assistance. They could be trained to detect defects in solar panels to help improve the power output from a solar farm. Or they could be trained to detect sharks at the surface of the water to prevent attacks at popular beaches.
 

How will your computer vision capabilities evolve?

We’re constantly improving our computer vision models to make our object detection and tracking features more performant, robust, and specialized. Today, drone operators will see greater detection accuracy with a head-on view, which often requires flying at a lower altitude. In the coming months, we’re working to optimize this capability to improve accuracy at higher altitudes and maximize the usability to users. Stay tuned for more updates!
 

Download SkyGrid Flight Control for free in the iPad App Store or learn more about our advanced enterprise features.

 

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 drones to air taxis, the urban air mobility market has advanced rapidly over the last two to three years. In fact, the FAA estimates 545,000 commercial drones will be in use by the end of 2020. These drones are performing real commercial tasks – they’re delivering packages, conducting industrial inspections, providing emergency assistance, and will eventually transport people.

But as more unmanned aircraft take flight, how do we ensure the safety and security of our airspace? I’ll shed light on four technologies that are critical to powering safe drone operations in 2020 and beyond.

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 will often 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 Blockchain Technology

The use of blockchain technologies will also be essential to the urban air mobility market. As a distributed ledger of immutable records, blockchain can ensure drone data and flight logs are stored securely and accurately.

Augmented with AI-powered “smart contracts”, which execute safely and under guarantees of performance, blockchain enables a verified data source airspace authorities can rely on when auditing drone operations or analyzing an incident. This approach allows 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 records on a blockchain 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.