By 2021, the sales of drones are projected to top $12 billion worldwide, with growth in the enterprise sector outpacing that of the consumer sector in both shipments and revenues. Aerial surveying, oil and mining, and agriculture have been the primary industries where drones have been both FAA-approved and utilized. Meanwhile, retailers like Amazon continue to make their case for drone use with regulators and policy makers. Suffice it to say that in this evolutionary environment, it isn't unforeseeable that requests for new technologies like drones will make their way onto the desks of CIOs for their strategic planning.

The technical and cost impacts on IT from drones and other "moving" Internet of Things (IoT) technologies are most likely to be felt in the areas of data collection/management and network bandwidth/capability.

SEE: Quick glossary: Internet of Things

Organizations are probably further along in the area of data collection and management than they are in their network planning. This is largely due to the number of big data initiatives that have been undertaken by enterprises over the past three to four years. Because of all these enterprise big data efforts, a majority of companies now have mechanisms in place to accept and process not only structured data from systems of record (SOR), but unstructured data in the forms of photos, videos, and documents, along with sensor- and machine-generated data that is likely to come from sources like drones.

So the major technical challenges for organizations choosing to use drones in their businesses will involve determining how to expand and invest in their network infrastructures to accommodate the constant streams of data that are likely to come from drone transmissions. Specifically, these challenges will be in the areas of data storage, security, bandwidth, and data transmission latency.

SEE: Drone policy

By way of illustration, Precision Hawk is a drone solutions provider whose drones most often collect Lidar (light detection and ranging), visual, and multispectral data (image data that is captured at specific electromagnetic frequencies, such as infrared). "We fly for many of the world's top agriculture and seed firms that are continually developing new phenotypes and traits," said Philip Ferguson, PhD, Precision Hawk vice president of product.

A phenotype is a set of observable characteristics of an individual element that results from the interaction between the genetic constitution of an element with the environment it is in. Phenotype research is undertaken by agricultural firms to understand which types of seeds and/or seed combinations grow best in certain environments.

"These companies use our multispectral sensors to evaluate phenotype performance at various growth stages throughout the year." Ferguson said. "They focus on particular events such as frosts or specific flowering stages. The multispectral surveys they produce, along with the added value from our algorithm market place, gives them the information they need to hone their phenotypes for production."

However, from a network standpoint, employing technology like multispectral surveys, which use images and sensors and can rapidly become highly complex amalgamations of data that are aggregated from a variety of sources, may create major challenges when it comes to collecting, processing, and transmitting such large data payloads.

"Managing data is still a challenge for the industry," Ferguson said. "With every new band comes more and more data to handle and process. Our clients' insatiable appetite for data is growing so quickly we have to create innovative solutions to support the bandwidth."

One solution to the problem has been ongoing work on the part of commercial drone providers to discover more effective ways to compress data for transmission, which lowers the risk of data latency and speeds the delivery of data--but that is not enough. Firms like Precision Hawk have also developed internal software that stores remote sensing data captured by drones, planes, and satellites in the cloud, where it can be processed and analyzed.

At the same time, major cloud providers like Microsoft (Azure) and Amazon (AWS) are starting to offer companies direct, dedicated, and redundant (for failover) data communications lines with high bandwidth and reduced latency.

SEE: Cloud platform spotlight: The top three contenders

Key points

What are the takeaways for setting IT strategy when it comes to new IoT deployments like drones?

1: Network architectures will need be revised

Do you invest internally in network management and bandwidth or do you consign some of these expansion projects to public or vendor-provided cloud services?

2: Enterprise data architecture will also likely need revision

Do you store your drone-generated data in an outside cloud, in the enterprise data center, or on an internal private cloud? How do you balance the need for eliminating data latency and delays in data transmissions with the equally important need for data security, which adds more latency to data transmissions?

3: Organizations shouldn't postpone strategy discussions

With a futuristic technology that is already on the horizon of implementation for many companies, it isn't too early for CIOs and other major IT decision makers to start discussing the technical and strategic implications of drone-based technologies with their CEOs and their boards. Drones will require new investments and commitments in IT. The sooner corporate stakeholders and decisions makers understand some of the mechanics and the requirements for using drones and other IoT technologies, the better they will be prepared to work with providers, regulators, and their ultimate customers.

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