Drone News & Articles

When Bill Herz wants to know how his crops are doing, he launches a drone.

He has nearly a thousand acres of corn and soybeans in LaSalle, eastern Illinois. "My drone has saved me time and energy," he says.

"I don't need to walk a whole field to find a problem area. I can fly the field, look at the results and go right to it."

Drones used for farming belong to the arsenal of tools used for precision agriculture - hi-tech farming using data to make better decisions.

So far, flying robots have enabled farmers to live stream crop growth, patrol for pathogens and boost farm efficiency. The next step is to recruit squadrons of them that can co-operate and carry out their tasks without the need for a human pilot.

Scientists from the Norwegian Defence Research Establishment (FFI) and the US's Rajant Corporation are working on simultaneously flying about 20 drones that can work in co-ordination with little human supervision.

A simple command is all that is needed for the robots to self-organise and communicate in a decentralised way, much in the way flocks of birds or schools of fish move around and interact with each other when they want to "solve" a task requiring collective intelligence.

  -  How swarming drones will change warfare?

  -  In the future, will farming be fully automated?

A Rajant-patented radio technology called "kinetic mesh" and "foreign function interface" distributed computing software are the technological ingredients behind this breakthrough.

"A typical drone of any size flies maybe 30 minutes or less," says Don Gilbreath, systems vice president at Rajant.

"If a farmer needs to map hundreds of acres of their field, it might take 50 battery charges. A swarm is essentially doing in parallel the same job up to 20 times faster than a single drone."

This "parallelisation of the workload" will single out healthy plants from sick ones and help farmers decide where to deliver more pesticides and nutrients, says Sondre Engebraten, a researcher at FFI.

"These fleets will result in us having more and better crops. We've got to feed the planet," Mr Gilbreath maintains.

With the world's population projected to reach 10 billion by 2050, consumption of agricultural produce is expected to increase 70%.

But while swarms of drones may seem to be one answer to this productivity challenge, Sridhar Tayur, professor of operations management at Carnegie Mellon University's Tepper School of Business, sounds a sceptical note.

"How do swarms work in bad weather?" he asks. "What is the amount of management and maintenance of the technology needed?"

Cost is another issue. Mr Gilbreath estimates that a drone swarm will cost tens of thousands of dollars once it hits the market, making it unlikely that smaller farmers in developing economies will be able to afford one.

"Why would a farmer in Vietnam or India, where there is cheap labour, where hundreds of people could go to every row and figure out which plants are sick and healthy, buy a swarm?" asks Prof Tayur.

"Large firms in industrialised countries will experience a cost advantage through increasing their output, with the smaller farmer left behind unless they form a co-operative of some sort with other micro-farmers or sell highly specialised commodities.

"These are economies of scale in action," he says.

Farmer Bill Herz admits that, as a small grower, he wouldn't pay tens of thousands for a swarm of drones. But as a consultant for a company providing hi-tech agronomy services, he would certainly consider advising larger growers to shell out the money.

And he thinks there will be a business opportunity for service providers to manage the flying and maintenance of the drones on behalf of large - and perhaps smaller - farms.

"Farmers won't need to buy the swarm," says Mr Gilbreath. "They may say, I need my field analysed by tomorrow. A service provider may come in with 10 or 20 of these things and do it by lunchtime."

In most countries, commercial drone pilots have to be certified by aviation authorities, so certified service providers would also overcome the regulatory hurdles famers would face.

Some, like Mr Engebraten and Mr Gilbreath, think farmers may be given special dispensations to use swarm drones, given that a drone crash in open farmland is far less risky than in a densely-populated urban area.

Drones grounded after crash near playing children

"There might be some proper training requirements and regulations for tracking and monitoring and noise, but I expect authorities will be reasonable," says Prof Tayur.

Next year, Mr Gilbreath and Mr Engebraten will be flying a fleet of up to 100 streamlined drones. They are currently tweaking their software and radio technology, making a drone platform tailored specifically to swarming and expanding the number of tasks the drone swarms can handle with a view to speeding up the process.

"If we tackle all these logistics and combine swarms with, say, autonomous tractors, it's not too far fetched to think that in the future we might have fully automated farming," says Mr Engebraten.

Unmanned Aerial Vehicles (UAVs) or drones are now being utilized to help elucidate factors that cause land surface temperature (LST) variability in the urban environment at small spatial scales.

Urban areas across the world are experiencing thermal stresses caused by the surface urban heat island (SUHI) effect- urban land surfaces experience higher temperatures than their surrounding rural areas. The replacement of undeveloped vegetated land with anthropogenic materials that absorb more solar radiation and have different heat capacity and surface-radiation properties resulting in higher surface temperatures that pose a significant threat to human health. It is critical that the fundamental processes that drive LST are understood in order to develop solutions that can protect human and environmental health.

Thermal remote sensing is an important tool for evaluating urban land surface temperatures. Data from satellites have been used to extensively study urban land surface temperatures and their effects. However, while satellite remote sensing is valuable for evaluating LST across a city scale, the spatial resolution precludes its applications to smaller spatial scales that better reflect the spatial complexity of the urban environment. Also, satellite remote sensing is temporally constrained to intervals between 1–14 days. Aerial flights do not have the same temporal constraints but would not be economically practical on-demand temporal resolutions.

Drones are a technology that can meet this challenge. Recent advances in UAVs and radiometric thermal cameras have enabled capturing LST on-demand and at sub-meter spatial resolutions that accurately reflect the spatial complexity and detail of land surface temperatures in the urban environment. UAVs also have advantages in that they can be flown on demand to capture LST at temporal resolutions unmatched by satellite or aerial imagery.

Researchers Joseph Naughton and Walter McDonald of the Department of Civil, Construction & Environmental Engineering, Marquette University, present a study to evaluate the variability of temperatures across urban land surfaces using a drone. In this study they applied a UAV and radiometric thermal camera to capture land surface temperatures at high-resolutions (13 cm) in two case study locations.

Visual imagery of the case study locations: Marquette University (a) and University of Texas El Paso (UTEP) (b). Visual imagery of Marquette was captured from a drone on 11 August 2018. Visual imagery of UTEP was pulled from Google Maps on 13 March 2019. 

Visual imagery of the case study locations: Marquette University (a) and University of Texas El Paso (UTEP) (b). Visual imagery of Marquette was captured from a drone on 11 August 2018. Visual imagery of UTEP was pulled from Google Maps on 13 March 2019.

(1) a portion of Marquette University’s campus in Milwaukee, WI and (2) a portion University of Texas El Paso’s (UTEP) campus in El Paso, Texas. The Marquette and UTEP case study areas were roughly 21,300 m2 and 27,300 m2, respectively and included a balance of both natural landscape and impervious gray surfaces. The study included:

• Quantifying land surface temperature variability across different surface types;
• Evaluating variance in temperature across different surface types based upon meteorological and/or other derived parameters (e.g., albedo, normalized difference vegetation index, apparent thermal inertia, etc.);
• Predicting land surface temperature based upon meteorological parameters and
• Assessing diurnal variability in land surface temperature magnitude and uncertainty.

Spatial distribution of temperature from a flight recorded on 11 July 2018 (a) and zoomed in spatial distribution of temperature for the concrete parking lot from a flight recorded on 11 July 2018 (b). The hotter surfaces (red) in the right image are parked cars and the cooler surfaces (blue) are heat shadows visible after parked cars leave. 

Spatial distribution of temperature from a flight recorded on 11 July 2018 (a) and zoomed in spatial distribution of temperature for the concrete parking lot from a flight recorded on 11 July 2018 (b). The hotter surfaces (red) in the right image are parked cars and the cooler surfaces (blue) are heat shadows visible after parked cars leave.

Spatial distribution of temperature (a), albedo (b), NDVI (c) and ATI (d) for a flight recorded on 11 August 2018. 

Spatial distribution of temperature (a), albedo (b), NDVI (c) and ATI (d) for a flight recorded on 11 August 2018.

Equipment:

Remote sensing data was collected using a DJI Matrice 100 (M100) quadcopter UAV. The M100 was deployed at the case study locations with three types of camera payloads—visual, multispectral and infrared. These cameras include the DJI Zenmuse X3 visual (12 MP), Zenmuse X3 multispectral (Blue-Green-NIR 680–800 nm at 12 MP) and DJI Zenmuse XTR radiometric thermal (13 mm, 30 Hz and spectral bandwidth of 7–13 µm). Additionally, ground temperatures were validated using a Nubee NUB8380 Digital Infrared Thermometer.

Conclusions:

According to the team the results revealed that land surface temperature variability is extensive and influenced by numerous variables related to urban environments and that air temperature and solar radiation are significant predictors of mean land surface temperature. Conclusions from this study hold true in both Milwaukee, WI and El Paso, TX, indicating they could be generalized to regions beyond these two case study locations.

The key findings from this study were:

Land surface variability was significant and ranged between (3.9–15.8 °C) for common land use types.

Areas that experienced pedestrian or vehicular traffic exhibited higher variability than comparable surfaces that did not. In Milwaukee, the high-traffic road had a coefficient of variation of 0.32 as compared to 0.08 for the low-traffic parking lot. This indicates that human traffic may impact land surface temperatures due to the heat-shadow effect.

Urban geometry has an influence on land surface temperatures; shadows and reflectance from buildings showed a significant influence on the temperatures of nearby land surfaces throughout the day. Sidewalk temperatures impacted by glass reflectance were on average 4.7 °C hotter that sidewalks not impacted by reflectance.

Land surface temperature variability is low in the morning, peaks at noon and goes back down in the evening. This may indicate that as surfaces heat up, they do so at different rates, which contributes to more variability during mid-day.

Air temperature and solar radiation were significant predictors of spatially averaged surface temperature in both of our models.

Data were consistent in the models between Milwaukee, WI and El Paso, TX, suggesting that the findings in this study may be generalized beyond the case study locations.

Citation: Evaluating the Variability of Urban Land Surface Temperatures Using Drone Observations, Joseph Naughton and Walter McDonald,

Department of Civil, Construction & Environmental Engineering, Marquette University, Remote Sens. 2019, 11(14), 1722; https://doi.org/10.3390/rs11141722, https://www.mdpi.com/2072-4292/11/14/1722/htm

SkyPixel and DJI are launching a $50k short film contest. The competition calls for 3-minute entries from gimbal users across three different categories. Entrants can use any gimbal or camera products, including DJI’s Osmo and Ronin series.

To celebrate the launch of the contest, DJI is offering discounted prices of $30 on Osmo Pocket & Expansion Kit Combo and a free extra battery with every Osmo Action purchased on DJI’s online store from 15th to 29th August 2019.

DJI & SkyPixel’s Short Film Contest: What’s the deal?

Since its inception in 2014, the SkyPixel platform has become a hub for aerial photographers and content creators from more than 140 countries. The platform’s previous contests have received over 150,000 submissions.

Much like those previous events, the Short Film Contest announced today invites users to submit their best work across three storytelling categories. For this contest, those are ‘Big Moments Start Small,’ ‘Make Your Move’ and ‘Adventure Starts With You.’

This is how DJI and SkyPixel have outlined those categories:

• Big Moments Start Small: Create a video showcasing the small, lightweight design of your camera device and your best cinematic scenes. Users are recommended to include at least 10 seconds of behind-the-scenes clips of their product such as DJI Osmo Pocket or other devices.

• Make Your Move: Create a video showcasing the stabilized footage from your device. Users are recommended to include at least 10 seconds of behind-the-scenes clips of their product such as DJI Osmo Series or other devices.

• Adventure Starts With You: Create a short, cinematic narrative film to showcase your creative skills and visual effects. Users are recommended to include at least 10 seconds of behind-the-scenes clips of their product such as DJI Ronin Series or other devices.

There is no restriction on the type or brand of equipment participants use. And you can submit as many videos as you like.

The 2019 SkyPixel Short Film Contest will entries from August 15 2019 to October 14 2019.

“DJI has redefined how people capture stable video for all of life’s moments. The compact size, portability and powerful imaging system of our Osmo and Ronin series have also made it possible for anyone to take their creativity and inspirations to the next level,” said Basile David, Director of Brand and Content Partnerships at DJI.

“With this contest, we hope to encourage more people to embrace and share their own creative way of storytelling.”

What are the prizes for DJI’s Short Film Contest?

There’ll be a total of 100 winners announced on October 31. The prize pool is worth a total of $48,600/€43,700 and you can see a full breakdown of what you could win, here.

The best entries will be showcased on the SkyPixel website and across DJI’s social media platforms.

Want to give it a shot? You can submit your 3-minute clips at any time up to October 14. Winners will be announced on Halloween.

Some incredible aerial pictures by Rockstar Photographers show how Budapest’s Hajógyári Island has been transformed, as hundreds of thousands of people arrived to Sziget Festival last week to listen to their favorite bands and party for a whole week. 

Here are some of the spectacular drone images and videos from the seven-day-long festival in the heart of Budapest:

LOS ANGELES (Reuters) - United Parcel Service Inc (UPS.N), the world’s largest package delivery firm, on Tuesday unveiled its drone delivery subsidiary and said it has applied for the Federal Aviation Administration certifications needed to expand the business.

The launch of UPS Flight Forward marks the latest move in the battle between UPS, Amazon.com Inc (AMZN.O) and Alphabet Inc (GOOGL.O) for the lead in the nascent U.S. drone delivery industry.

UPS said Flight Forward could receive FAA certification for multiple drones and pilots as early as this year, potentially becoming the first company to win such approvals.

UPS is “laying the foundation” for a sustainable drone delivery business, said Bala Ganesh, vice president of the Advanced Technology Group at UPS.

The Atlanta-based company plans to roll its revenue-generating hospital project with drone partner Matternet into Flight Forward.

UPS and Matternet run five to 10 daily drone flights that transport human medical specimens for WakeMed Health & Hospitals in Raleigh, North Carolina. The drone flights carry blood and tissue samples from various points around WakeMed’s main hospital campus the short distance to its central laboratory.

Ganesh declined to say how much revenue the WakeMed deal generates. UPS plans to expand the scope of its WakeMed delivery business as it recruits other hospital customers.

Flight Forward is targeting healthcare companies as part of an ongoing UPS effort to use higher-profit specialty deliveries to offset the margin squeeze from booming residential e-commerce deliveries.

Reggie Govan, who was chief counsel at the FAA during the Obama administration, said there are significant hurdles to overcome before an army of drones can drop packages at U.S. homes and businesses.

It requires a “more sophisticated and robust technology and regulatory framework than currently exists, including more direct regulation by state and local governments than either the FAA or industry has yet to realize,” Govan said.  

Nevertheless, Govan said, every new step forward “helps to move us from one-off deliveries of toothbrushes, coffee and pizza.”

Alphabet’s Wing got a jump on rivals earlier this year when the sister unit of search engine Google became the first company to get U.S. air carrier certification for a single-pilot operation.

Amazon, known for its splashy drone delivery tests, said in June it is building fully electric drones. Amazon has “numerous experimental certifications” to test and evaluate its systems.

UPS, Wing and Amazon Prime Air are among the corporate and government entities with seats on the FAA’s Drone Advisory Committee.

In the not too distant future, getting a pizza delivered might mean a drone flies it to you.

This would have been unthinkable even a decade ago, but aviation regulators have approved commercial drone trials in places like Japan and Australia. After getting the green light in April this year, Google’s parent company Alphabet launched its commercial air delivery business Wing in Australia’s capital Canberra, where it delivers burritos, coffees, pet treats, golf balls and more via drones.

It’s exciting times, but what does this have to do with ageing populations or real estate? As you probably know, Asia Pacific and the other parts of the world are facing rapidly ageing populations, presenting real challenges for communities and their economies.

In a recent report, M&G Real Estate’s research team suggests property investors can take advantage of the increasing take-up of e-commerce to unlock the “silver dollar”. Elderly people, who tend to have more disposable income than working-age people but are often less mobile, are increasingly using home delivery already.

As more and more people turn to online shopping and home delivery, the increased demand will only exacerbate existing labour shortage pressures facing the logistics industry, however drones or autonomous vehicles could be the answer. Jonathan Hsu, APAC head of research at M&G Real Estate, tells APAC Real Estate what this all means for real estate investors:

How can property investors take advantage of the developments in drone delivery today?

JH: To reap the benefits from the development of drone delivery, investors should start focusing on the last-mile logistics facilities servicing suburban/rural customers and central/dark kitchen fulfilling food delivery orders. For logistics facilities, drone delivery would allow businesses to reach consumers in more suburban and rural markets with increased efficiency and speed.

This could potentially increase demand by consumers for home delivery, and in turn bolster demand for more logistics space to fulfil these increased orders. Whereas for central/dark kitchens that support food delivery, using drones for food delivery could also lead to increased demand for central/dark kitchens for food preparation and delivery; these kitchens could be located in industrial properties, suburban shopping centres, or carpark space.

Investors may plan ahead for drone delivery by working with key tenants that are looking to implement drone delivery in the near future. There may also be opportunities for higher specification, built-to-suit for investors to secure long-term income streams with innovative tenant-partners.

What are the risks/challenges that drone delivery present to real estate investors?

JH: Given that it is still early days, investors would need to keep abreast of the local regulations and infrastructure improvements that govern and facilitate drone deliveries, be it to commercial or residential areas to better assess the risks and opportunities for real estate.  Updated regulations and infrastructure are likely to be the key to the wider adoption of drones for delivery.

Drone delivery may require real estate owners to retrofit existing warehouse facilities with newer power generators to ensure battery-operated drones have consistent access to electricity.  For urban drone delivery centres, there may be zoning issues that bar certain warehouse locations from launching drone services.

As to whether it would hurt bricks-and-mortar retail even more would largely depends on the cost of drone delivery for retailers to fulfil online sales. Currently, it has been reported that online orders are costing retailers more than store-sales due to the associated costs of delivering purchases to consumers, particularly for the ‘last mile’. Should drone delivery help to reduce last-mile costs significantly and is an option available to most retailers, it is likely that retailers might be further pressed to evaluate their physical store networks in relation to their online business.

What other real estate sectors will ageing populations across Asia Pacific have an impact on?

JH: Overall, ageing populations are likely to benefit sectors such as specialized logistics, healthcare and [senior] living.  This is not only region-specific to Asia Pacific, but also pertaining to the impact of the ageing population globally.

Increasing demand for specialised logistics assets catering to fresh groceries and medical supplies are expected to be driven by rising delivery demand to aged seniors out of convenience and accessibility needs.  These more temperature sensitive items will require climate-controlled cold storage facilities that prevent fresh foods and medication from spoiling.

Health-care related properties such as medical offices and hospitals are also expected to see increased demand that follows the steadily increase in ageing population.  Senior housing catering to aged living and assisted living segments should continue to expand with increasing demand as well.

In smaller rural cities, the residential sector may be negatively impacted by dwindling population, or relocation of the [older] population to larger urban cities.  For the older generation, access to amenities, healthcare and convenience may motivate many to settle back into the urban setting.

The rise of an ageing population across cities is also likely to have an impact on the design and place-making of properties, as increasingly elder-friendly fit-outs would be required, be it in shopping centres or offices. This may subsequently have an impact on operating and capital expenditure as buildings go through refurbishments to cater for this growing segment.

Visual inspections and steel thickness measurements are key elements of renewal surveys. Preparing ships for these activities is time-consuming and costly. DNV GL now offers a fast-track solution using drones.

DNV GL has been using camera-equipped drones in surveys since 2016. The concept, the technique and the equipment were developed by the surveyor team in Gdansk in response to customer enquiries. A traditional survey requires rafting, roping­ or staging so the inspection personnel can reach all relevant structural elements. Rafting takes additional time to ballast and de-ballast the vessel; both roping and rafting often require voyage surveying. Setting up staging can even take days.

New tools for remote surveys

This disproportionate effort caused owners to inquire about alternative methods. In addition, staging often damages surfaces and coatings that must be repaired. In certain situations owners have to hire subcontractors providing rope access techniques, an especially hazardous type of work.

These conventional inspection methods put ships off-hire for weeks, which means lost income. Logically owners have an interest in keeping these times as short as possible. This led to the idea of using drones. “We started the drone project in 2015 to make surveying smarter, more efficient and economical for the owner, and safer for surveyors,” says Tomasz Oledzki, Head of Section Fleet in Service (FiS) Poland at DNV GL ‒ Maritime. The first step was to attach a high-resolution camera to a drone so surveyors could take a close look at hard-to-reach places. Several off-the-shelf drone models were tested. The team ultimately chose a medium-sized model for interior inspections, and a larger, more powerful one for outdoor inspections where wind can make positioning and controlling the drone more difficult, for example on offshore platforms.

The result of six months of development work and trials: A mid-sized commercial drone fitted with a special accessory frame designed and manufactured in-house by the Gdansk DNV GL surveyor team is now standard equipment for inspections at DNV GL locations around the world.

A new dimension: thickness measurements

“We now have three years’ experience performing camera-assisted visual inspections on ships and offshore structures using drones,” Oledzki continues. “But our customers expect more. They would like us to cover the full scope of inspections using this advanced technology, including thickness measurements. So in mid-2018 we decided to venture into this field and began developing a flying thickness measurement system. We built several prototypes and finally arrived at a design that satisfied our requirements.”

An attachment frame was engineered in-house by the Gdansk team in an iterative process including repeated practical testing. Its design is compact and ‘universal’, allowing surveyors to interchange the close-up inspection camera for the ultrasonic measurement head on a drone at any time, or attach the frame to another drone in case the original one is damaged. This standardization minimizes the amount of equipment surveyors have to carry when travelling to a ship, especially when dispatched by helicopter. “Reducing the amount of luggage was actually our key objective when developing this system,” stresses Oledzki.

What is more, key parts of the attachment frame are made by the DNV GL team on a 3D printer, which means the team can now manufacture any number of identical frames in a repeatable process, whether for their colleagues at other DNV GL offices or for spare parts.

Bottom-line value for owners

“We have successfully tested the new thickness measurement drone on an MPV, some bulk carriers and this shuttle tanker,” says Oledzki. “The results are very positive – the system works well and delivers reliable data. Today we can say we have the capability to offer owners the full package of drone-assisted remote survey services including close-up inspection and verification of the thickness measurements.”

Alba adds: “We see a great opportunity to accelerate the survey process and minimize off-hire times; what is more, we can actually perform some inspections during the voyage of a vessel when cargo spaces are accessible. This is of great value to owners and operators.”

The biggest challenge the Gdansk team faces is to convince ship and cargo owners that the new methods delivers good and reliable results, says Alba. But the response from customers is excellent: “The owners for whom we have performed drone surveys to date have been very satisfied, and in many cases they were outright surprised how quickly and efficiently inspections can be done, and how little owner involvement is required to provide access to the structure. Whereas in the past, the surveyor had to be physically taken to the structural element to be inspected, the drone now ‘brings the structure to the surveyor’ for real-time inspection.”

Limitations and opportunities

Yet owners should not foster unrealistic expectations, Leszek Alba cautions: “The critical point is the condition of the vessel interior.” Oledzki explains: “When we receive a request from an owner for a drone inspection, we take our equipment on board and first assess the condition of the vessel to see whether thickness measurements can be done with the drone. If the coating is intact and the surfaces are clean, we can get good visual inspection results and high-quality thickness readings. If the condition of the vessel is not suitable for ultrasonic thickness measurements, we can still use the drone with a mounted camera to perform a visual inspection.”

“Drone or not, it is impossible to take ultrasonic measurements on corroded steel because the measurement head is unable establish direct contact with the steel to get a reading,” stresses Alba. “Ultrasonic measurements are suitable to confirm the intact condition of structures. Our drone inspections serve the purpose of verifying the good condition. They are ideal for renewal surveys of younger vessels that are five to ten years old.”

The classification rules require a wide range of thickness measurements, most of which are typically performed by subcontractors. “It is important to note that our measurements are only supplemental to what the contractors are doing,” Alba points out. “We only access structures that cannot be reached by conventional means. We use drones to perform close-up surveys and to verify and confirm that a ship is structurally in good condition as required under class rules. The drone accelerates this spot-checking process dramatically so we can accomplish it within a single visit. We can even perform it during a voyage or port stay.” Wherever conditions are detected that warrant further investigation, traditional access using staging is unavoidable, he adds; but when the drone survey shows that everything is in good condition, this expense can be avoided.

An evolving technology

Younger tankers, MPVs and bulk carriers are the primary targets of DNV GL’s drone survey offer. Oledzki says that conceivably drone measurements could be extended to cover the full scope of thickness measurements at some time in future. And that is by no means all this technology could accomplish. “The last step of this development could be autonomous drones performing close-up inspections and thickness measurements,” says Leszek Alba. “They could either navigate based on sensor and navigational algorithms or using an electronic model such as the ‘digital twin’. This would enable the surveyor to stay outside, simply watching the computer screen and letting the drone do its work independently.” A research programme in Oslo is underway to investigate these possibilities, and there are even scientific studies in progress to identify potential contactless thickness measurement technologies.

As for the present, incorporating thickness measurements in drone surveys is already a big step, says Alba: “Today we have gathered enough experience and solid results to know what we can achieve in assessing the condition of structures. Autonomous drones will essentially do the same but with less operator involvement.” DNV GL as a classification society offers the unique advantage of providing not only drone-based visual and thickness inspections but also the know-how and experience to interpret the data: “We know the ship, and as surveyors we know exactly what we are looking for,” says Tomasz Oledzki. “We not only take pictures or measurements but we are competent to assess them and confirm the good condition of the ship, and we take responsibility for every aspect of these services. We provide one-stop shopping to owners.”

When you combine the words data and mining together you might think IT and technology focused initiatives aimed at extracting value from data in the enterprise. But sometimes we actually mean applying the power of data and intelligence to the actual mining industry, where the primary value being extracted are resources from the earth. Even in this very physical of industries, artificial intelligence and machine learning are being applied to increase the efficiency, effectiveness, environmental and safety concerns, and other aspects to help continue to make mining a valuable enterprise.

Mining has matured significantly as an industry over the past century. No longer are we mining with physical hand and animal labor, extracting crucial resources by pickaxe and oil lantern. Modern mines are now sophisticated, machine-intensive environments that put heavy equipment and computer-driven technology in close proximity to the humans that need to operate them. Whether we’re extracting minerals and ores such as copper, iron, gold, or energy-rich deposits such as coal, oil, or gas, machines are needed to extract the mineral resources from the earth, transport them to the surface, prepare them for refining or transport, and move them to the destinations where they can be further refined. Because of how dependent we are on these natural resources for many parts of our lives, the operations behind mining have gotten quite complex.

The act of extracting minerals from the earth is quite disruptive to the environment. When we mine or drill, we are digging deep into the Earth and pulling out resources. We also have to extract the debris around it and manage piles of waste material generated from the mining process. Often, managing the environmental aspects of mining can be just as time and cost intensive as extracting the resources themselves. Artificial intelligence is helping to transform the mining industry into a safer, more profitable, and more environmentally friendly industry.

Improving resource discovery and planning with AI

Mining is a very costly undertaking. In order to minimize the initial investment, mining companies need to be very precise about where and how they dig. One of the ways that the mining industry is utilizing AI is to learn more about the terrain that they are working with. The computer is able to much more precisely map out and predict terrain than a human.  Most of the time we have to dig our way to the resources in the first place. That requires significant investment. An error in mining in the wrong location can cost millions or billions of dollars. AI can help us better prevent those errors.

Artificial intelligence is also being used to identify new and potentially valuable areas to mine or drill. Through the use of pattern matching, predictive analytics, and even computer vision systems that can process map and geological data AI is able to analyze vast quantities of data to better predict where to find better resources. With better predictions comes better planning and a better return on investment.

AI is becoming a powerful tool for analyzing data of all kinds in the mining industry. Most industries use machine learning and artificial intelligence to analyze their data in operations, ranging from managing transport and logistics to human resources and supply chain management. Machine learning can spot patterns that are useful in reducing expenses, optimizing resources, and reducing waste.

Intelligent drones and autonomous machines

Drones are increasingly being used in the mining industry, becoming a very powerful tool for a wide range of applications. Companies are using drones to scan over their mining operations, keeping an eye on quarry and waste piles, environmental issues, retention and leaching ponds, and pipeline infrastructure. Much of what can be seen with a drone cannot be seen with our eyes on the ground. From the sky progress can be monitored as well as the mine’s impact on the ecosystem around it. Using machine learning-based computer vision systems, these drones can analyze data collected from the imagery. This gives mining companies continuous, around-the-clock access and monitoring to their facilities in ways not possible with human operation.

Mines have always been dangerous places to work. However, to extract the resources we need, we’re moving to increasingly more hostile environments to get them. Whether we’re extracting coal or minerals miles under the earth, or oil and gas from deep sea drills, or excavating land in arctic zones, we’re increasingly putting people into harsh environments. It is much more preferable to put machines and equipment into mines and greatly minimize or eliminate human labor from these harsh conditions. Through the use of AI-powered autonomous systems, mining and energy companies are making greater use of self-controlling machines in harsh environments. This equipment is then able to work without the presence of a human. It is also capable of going to many places that humans just can’t physically go.

Autonomous mining equipment is set to increase overall productivity. In addition, these machines are able to work around the clock without tiring while also minimizing costly and potentially fatal mistakes. If a machine gets stuck in a mine we can always retrieve it at a later time and date without worrying about it dying. We can’t do the same with a human. Because of this, Komatsu Mining has built a wide range of AI-powered autonomous equipment being used in a variety of hostile environments. Some of these machines are autonomous excavators while others are autonomous transportation and loading vehicles.  Many modern mining companies operate the “digital mine” which connects the equipment with each other, uses intelligent technology to decentralize control, and minimizes human labor. Autonomous vehicles are part of what is called as a digital mine.

Another aspect of these autonomous machines is that they can perform some of the regular inspections needed on the mines. By attaching cameras and sensors to the equipment companies can detect issues in the mine such as gas levels and structural instability. The more frequently that mines can be inspected and the less we need to send human inspectors into a mine, the safer the mining operation is. 

Reducing environmental impact with AI

Mining by its nature is destructive and has a negative environmental impact. While it isn’t possible to completely eliminate the negative environmental impact of mining, it is possible to significantly reduce this impact by managing how resources are extracted, transported, and treated.  Cameras and sensors are being deployed around mines, both on the inside and outside to have constant surveillance. These devices are able to monitor excavation, extraction, and general mining activities, keeping tabs on the spread of waste and harmful materials.

What makes AI monitored devices different from “dumb” devices is the analysis of the data. These AI enabled devices are capable of instantly analyzing and interpreting large volumes of sensor data, and alerting when an issue is present. These systems can spot patterns that may be of concern. Regular tremors, temperature changes, and events across multiple parts of the mine can all be recognized by machine learning.

Artificial intelligence has had a broad impact on the mining industry. Mining equipment manufacturers and development companies are increasingly making use of AI to provide greater value and reliability to the industry while also increasing safety and reducing environmental impact. The impact AI is already having is being shown through safer mines, reduced impact on the environment, improved economics and profitability, and increased extraction of precious resources.

Humans and satellites have a hard time beating a drone’s eye for detail in scanning farming systems from above. Flying below the clouds, collecting and sending images in almost real-time, unmanned aerial vehicles (UAVs) gained ground quickly in agriculture in the last decade as part of so-called precision agriculture. Among their wide range of applications, they can help farmers check crops’ health, track livestock, plan fertilization, assess damages, and map fields at high-resolution. A growing number of drone models for agriculture are sold on every continent — but many experts question whether drones fulfill the needs of all farmers across the world.

While the United States, the United Kingdom and Australia have increasingly embraced agri-tech, developing countries, where farm sizes average around 2.5 acres, have been slower adopters. Making drones work for smallholders remains an issue, explains Joseph Messina, professor of geography at Michigan State University. "One of the challenges is how to translate drone technology into something that gives useful information to farmers," says Messina to Food Tank.

Investments in agricultural drones grew by 344 percent between 2013 and 2015, says a report from market researcher Ipsos, leading to drops in the once prohibitive drone price tag. The cost of running a basic agricultural drone dropped by five times over the last five years, from $50,000 to $10,000, explains Messina, making more smallholders able to afford UAVs.

"But it’s another thing to tell them something actually useful [using drones]," says Messina. The data drones provide boils down to plant health and a little bit on the environment, he explains. Drone-collected images might tell farmers where to fertilize, whether to spray pesticides or where their equipment has failed. "Industrial farmers have more resources to address problems quickly," Messina explains, but smallholders in developing countries have fewer solutions at hand.

Industrial farmers have more resources to address problems quickly, but smallholders in developing countries have fewer solutions at hand.

As a smallholder farmer in a developing country, "you can go out into the field and weed yourself or you go to town for waged labor," says Messina to Food Tank; however, drones offer small farmers an advantage by facilitating early decision-making, allowing them to spot issues sooner through drone data than through the human eye.

Drones’ ability to fly under the clouds, where satellites don’t reach "is huge, especially for the Global South," Messina explains. "You can process shadow much more easily than through the clouds; in rain-fed environments that was much more useful than I expected."

"Drones can identify locations where you can make sustainable choices for the smallholder," says Messina to Food Tank. Drones can help small farms tackle soil loss by spotting degraded land needing restoration with planted trees and resulting green manure — a fertilizer made up of fallen leaves or uprooted plants that are plowed back into the soil to deliver nutrients. "It’s a good way to improve soil structure by collecting the leaves and working them into the ground," says Messina.

But small plots can still limit drones’ capabilities. Monoculture systems are easier to assess, says Messina, with crops such as corn being highly suited for management via drones. In developing countries, farmers tend to plant a large diversity of crops over their few acres, which can be problematic. "In Malawi [our researchers] mostly looked at maize, pigeon peas and pumpkins, and they are easy to identify. With plants that are very similar — such as sorghum and maize in their different growth stages — you have to know what is there before making an assessment," argues Messina. For indigenous crops that lack a long history of development, such as teff, "there is greater uncertainty with the technology, but you would be able to identify problems in the crop more quickly with drones," Messina says.

Across Sub-Saharan countries, the African Union has supported the spread of commercial drones for agriculture through the Eyes In The Sky, Smart Techs on the Ground project, led by the Technical Centrer for Agricultural and Rural Cooperation (CTA). But in its report on drones, the same body points out that while drone research focuses mainly on the kind of information technology can provide, it’s not looking enough at what interventions make drones cost-effective for African smallholders ― who have little land, tenure issues and a multitude of farming systems.

The legal landscape for drones is also problematic. While in the United States drone operations are heavily regulated — mainly for safety reasons, Messina says — the low altitude imposed on flights prevent them from covering large areas. Only about 26 percent of African countries have laws targeting UAVs, states the African Union; across the continent, the lack of legal clarity, harsh restrictions, or temporary bans of UAVs until laws are enforced are slowing the industry’s takeoff. As neighboring countries such as Tanzania, Malawi and Mozambique regulate drones differently, "your ability to come up with something that might work across all of these environments decreases," says Messina.

"We are trying to come up with solutions so we can ultimately give information to the farmer quickly enough for them to make decisions,” says Messina to Food Tank. "Many times we focus on this developed-world lens, without recognizing somewhere else a farmer will go and do this by hand."

An aerial project to capture wildlife and trees across the Emirates has completed its first phase, giving a fascinating statistical insight into the country's natural habitat.

Every fruit tree and ghaf tree, water well and farm is being mapped to support future planning.

The environment ministry operation covered 550 sq km of agricultural lands across Dubai, Sharjah, Ajman, and Umm Al Quwain, providing "a wealth of raw information that is being analysed through leveraging AI technology".

The data collected using drones indicated the presence of 5,637 farms - 895 growing crops and 2,919 rearing animals.

The crop farms consist of 35,535 fruit trees and 200,230 trees that serve as windbreakers. The survey also tracked the presence of 5,635 farm buildings - labour accommodation, barns, and warehouses, among others - 362 wells, and 3,447 protected farms - 2,635 of them use netting to protect their crops. Ghaf trees accounted for 73,344 of all trees on these farms.

Phase two of the project is scheduled to run from October to December, and will map agricultural areas in Fujairah and Ras Al Khaimah.

The project will ensure crops, livestock, and mixed farms as well as cooled and regular greenhouses, soil type and condition, and crop diseases are accounted for.

Dr Thani Al Zeyoudi, Minister of Climate Change and Environment, said the mission will "establish an accurate database of actionable statistical information to inform decision making and planning", he said

"The move will help us optimise the allocation of natural resources and expand sustainable agriculture".

Farming in the UAE is extremely water intensive and inefficient operations drain valuable sources like groundwater wells.

Officials aim to gain an accurate estimate of the volume of irrigation water used by agricultural holdings and plan ways to alleviate the pressure on groundwater through deploying sustainable irrigation.