How The Drone Industry Evolve In 2018

Drones in 2018

Drones are a perfect example of how our technology has evolved and will continue to grow in the future. So, what exactly does it offer? For casual users, it is just a fun toy. However, drones have use cases in multiple fields, including safety, health, and industry.

Until now, drones have gone on a wild ride. It has been massively regulated by U.S. government considering the threats that it brings including spying. Moreover, drone safety had been a significant issue. But to completely understand drones, we need to understand both its advantages and disadvantages before making a final call on how they should be regulated.

For starters, there are good drones and destructive drones. Those drones that are created for good are being used to save lives, help improve business efficiency and use autonomous control so that the human limitation can be removed. Destructive or bad drones do the exact opposite and are harmful in one way or another.

In this article, I will try to understand the future of drones from the perspective of tech, security, and innovation.

Drone Technology

Drones have evolved rapidly in the last decade or so. However, drones are not new and existed from the 1930s. The modern era of drones started after 2001, and it is now slowly becoming part of our daily life. You can now own a drone only if your state laws allow you to do so.

So, what is next for drones? The answer depends on how artificial intelligence (A.I) can be used to make drones more useful. A.I. can help drones overcome the human limitation and make drones more useful in different sectors including industry, tech, delivery and so on. However, A.I. powered drones can also be used to kill humans, deliver drugs or worse spy on someone.

There has already been a lot of debate on how A.I. can provide drones with ultimate power. Elon Musk also called out on the ban on killer robots which can also include drones. But, we have to weigh the gains over a possible loss and should be used to improve the different levels of transportation, accessibility, and overall growth.

Drones can now be programmed to learn from mistakes. Learn to Fly by Crashing, a paper published by Carnegie Mellon University explores how AR drones 2.0  are learning by learning from their own mistakes. This is just one use case of how A.I. and big data are going to impact drones in future.

Another critical use case of drones that are going to evolve and get implemented is their use in the industry. Many big companies will use drones to inspect their infrastructure and send direct reports to the system. Furthermore, they are also equally useful for surveillance purposes. The delivery system will continue to be refined in future as currently, Amazon is testing the use of drones to improve the delivery system. Jeff Bezos, Founder & CEO of Amazon, says that the aim is to get items delivered in “60 minutes.

Regulatory Reform

Government regulations on drones have always been tight. However, 2018 can be the year when the laws become less stringent. The current regulations from Federal Aviation Administration (FAA) regulate drones such that they must be used within human sight. However, this regulation is binding at many levels as it will not allow commercial companies such as Amazon to use drones in their operation.

In 2017, the general perception towards drones changed as well as their purpose as such in recent natural disasters, fortifying their benefits. Now that change is progressing; the FAA needs to take note and began to set appropriate regulations for the future of this industry. Drones manufacturers will also play a role, by ensuring that their drones can navigate safely through an environment, especially rooftops, humans, vehicles, etc. To achieve this, current technologies need to be adapted to allow for autonomous navigation and self-learning capabilities.

Final Thoughts

Drones have evolved remarkably in the last decade or two. The commercial usage will only propel it towards mass adoption. 2017 has been the year where it is now impossible to ignore the benefit in natural disasters management and commercial spaces. With relaxation in regulations, more and more industries will adopt drones.

One more thing is how blockchain can be used to revolutionize drones. Recently, blockchain is impacting almost every industry. Drones can be the next thing that can utilize blockchain technology. We only have to wait and see if blockchain powered drones can become more secure, accurate and easily regulatable.

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How IoT will evolve this year and why disposability and recyclability will determine the future

The year is shaping up to be one of the most innovative in history, and you may be wondering which trends will emerge to drive connected life forward. After we saw IoT become a household name in 2017, says Vivek Mohan, director of Wireless IoT Products at Semtech, here’s what I believe 2018 has in store.

As people try to find greener and more energy-efficient methods, energy harvesting will be important in the Internet of Things (IoT), especially for low-power technology. This will have particular relevance with solar power, thermal energy, wind energy, salinity gradients, and kinetic energy captured and then stored for small, wireless autonomous devices like those used in wearable electronics. Wireless sensor networks will take on added significance as these new cutting-edge IoT technologies are developed.

Field services

The field service industry is huge, encompassing 20 million field technicians spread across the world. These individuals are responsible for maintaining everything from hospital equipment, to office elevators and heavy manufacturing machines. Maintenance can be a daunting and costly task, so creating efficiencies and leveraging predictive maintenance is crucial. IoT technology such as sensors and real-time monitoring are becoming more crucial because organisations need to know exactly where and when equipment needs to be adjusted or replaced.

Keeping rodents and pests, such as rats, mice and termites, away is an age-old problem that has deep consequences when it comes to meeting food and building safety requirements.

Leveraging sensors with IoT devices and networks is becoming more prevalent, and in the year ahead we will see even more creative applications of this technology for monitoring of pests, so people and businesses can detect possible problems before they become serious.

Disposable IoT

However, by far the biggest trend that I believe we will see this year will be the rise of disposable IoT. As IoT become more mainstream, new types of use cases and applications appear that require low-cost and low-power solutions with the ease of one-time usage.

Disposable technologies are not a new concept (think disposable cameras), but disposable technologies for IoT is new. The concept of disposable IoT is in its infancy, yet we are starting to see innovation in this area from large industries.

For example, the U.S. Marine Corps is now testing single-use drones made of cardboard, powered by inexpensive motors, to deliver supplies to combat troops. Tech companies have also begun using low-cost, low-power, green tags that can track real-time feedback.

Various challenges needed to be met before truly disposable IoT could become reality. Firstly, the diversity of the types of application that exist within IoT and the subsequent need for multiple types of technology – and the adaptation of others – has posed perhaps the biggest hurdle.

A further challenge has been related to the battery. Indeed, a key issue with IoT stems from the fact that many devices require batteries, but these energy sources need to incorporate materials with much lower levels of toxicity than, for instance, lithium-ion batteries, which are difficult to recycle. I’ve seen this innovation up close, as Semtech recently invested […]

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Letter from Ethiopia: Can We Use Technology to Help Privacy Evolve?

I’m writing from Addis Ababa, where the African Union’s Specialist Technical Committee on ICT is having its biannual conference. I won’t report on that, as it’s still happening, but I can report that some of the hallway conversations have been both interesting and reassuring.

The topic of privacy came up over coffee, of course – and I was glad to hear that it is not only seen as a key issue for technology and governance, but it’s also seen as being closely interconnected with issues of cybersecurity. As readers of the Internet Society’s blogs will know, we think so too. You can’t have good privacy if you don’t have good security tools, and you can’t have good security in the absence of privacy.

As you would expect in a continent with all of Africa’s rich diversity, the cultural and social approaches to privacy can also vary widely, and people face exactly the same challenges as elsewhere, about how to translate them into workable technical and governance solutions. Today I will have a few minutes to set out some thoughts on that, in one of the afternoon sessions. I plan to suggest that we keep asking the “why?” question. Why are we trying to codify data protection? Why are data subjects’ rights important and worth fighting for?

I think if we ask “why?”, we eventually get past the “because the law says so” layer, and down to the layers that tell us why privacy is important to the individual. How do individuals and societies benefit, if they respect the so-called “private sphere” of life… and what do they forfeit if they allow it to be eroded?

These are big questions. They touch on rights, and self-determination, and autonomy – and, if you think about it, those are all areas in which the machines are chipping away at us humans. As a pedestrian, what are your rights if a self-driving car decides that you are the path of least damage in a collision? How much self-determination do you really have, in a world of behavioural advertising and curated content? How much autonomy do you have, in a world where algorithms make decisions that can affect your health and livelihood? And what, if anything, can we humans do about it?

Let me make two assertions:

First: technology’s current direction of travel is one that erodes our direct control over events around us.

Second: we are increasingly impacted, not by our own actions, but by data that comes from the actions of others. That, after all, is what targeted advertising is: it’s the impact, on you, of things other people did, said and bought.

If those two assertions are true, then the key to my privacy has to lie in my ability to influence the behaviour of those who hold data that can affect me. Up to now, regulation has tended to focus on the rights I have concerning data that is about me – rather than data that can affect me. The two are not the same, though, and the shift from “personally identifiable data” to “privacy impacting data” has profound implications. If you think about it, most privacy regulations up to now have been called “data protection” laws. Doesn’t that tell us that the focus isn’t quite right? Rather than legislating to protect the data, is it possible to legislate to protect the individual against harmful effects of the use of data, regardless of who that data is “about”?

I’ll freely admit, I don’t have answers, let alone simple or easy ones. But it’s clear to me that our current thinking about privacy has shortcomings, and if those shortcomings put our privacy further at risk, I want to deal with them. I hope I will get some initial reactions on Wednesday from what may well be a somewhat bemused audience – but I also hope I will get some reactions from you, here. Please let me know what you think. Is privacy, as we know it, as dead as various white male businessmen have told us, or can humans use technology to help privacy evolve?

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LTE – A Continuing To Evolve Towards 5G

LTE – A Continuing To Evolve Towards 5G

When we talk about network evolution it is by no means all about 5G. Despite all the resources being poured into developing the technology for the next generation of mobile communications users, there are still new features that are being introduced to LTE-A which will continue to push performance boundaries up until and even beyond the launch of 5G services. Staying true to its full name (Long Term Evolution), the LTE/LTE-Advanced technology standards are still growing and evolving. New networks are still being rolled out, and leading-edge features are being added to 4G to satisfy the market need for ever-increasing data rates.

Evolving with 5G

There are three main ways in which LTE-A is evolving towards 5G. The first is by improving user throughput for small cells by the use of higher modulations schemes in combination with higher order carrier aggregation. Secondly, the ongoing improvements in interference, cell coverage and system throughput, are being achieved with the introduction of features such as CoMP (Coordinated Multipoint transmission/reception) and feICIC (further enhanced Inter-Cell Interference Coordination) which offer improvements in cell edge performance. The third one is the introduction of low complexity type user equipment (UE) for IoT applications, a development that is already happening under LTE-A with the introduction of NB-IoT as well as Cat-0 and Cat-M. These new protocols will place tighter specifications on systems signaling in requirements to accommodate large numbers of UEs.

The challenges

One of the major challenges for wireless network validation is to keep up with the increasingly and rapid introduction of new features in the roadmap of 3GPP LTE-A as we move through specifications that are already starting to look remarkably like some of the 5G targets. At its inception LTE used just a single 20 MHz carrier, and its performance only started to meet the IMT targets for 4G in real world scenarios when LTE-Advanced (LTE-A) features were progressively added to it. The first enhancement was carrier aggregation, which combines blocks of spectrum known as component carriers (CC), enabling the use of fragmented spectrum to increase data rates – initially combining two carriers (2CC) but now being introduced for up to 5CC, and also combining time division duplexing (TDD) and frequency-division duplexing (FDD) spectrum. Other features introduced were: Higher Order MIMO, which allows increased spectral efficiency to be achieved; Relays – which extend coverage in areas where wired backhaul is uneconomical; and Self-Organizing/Self-Optimizing Networks (SON), which enable the efficient use of heterogeneous networks (HetNets) that improve the coverage and capacity provided by traditional macro base stations.

Higher levels of modulation density, such as 256 QAM, have already pushed up the achievable data rate to 1.6 Gbps when used in combination with carrier aggregation and 4×4 MIMO. The aggregation of higher numbers of component carriers is pushing this still further: the highest downlink data rate theoretically available is 3.917 Gbps, which combines 256 QAM with 8×8 MIMO and 5CC aggregation.

Interference and implications

There was also a successive introduction of Interference Management (IM) functionality with increasing levels of sophistication, enabling increased area spectral efficiency to be achieved. ICIC (Inter-Cell Interference Coordination), which reduced interference at the cell edges, was first evolved to eICIC (enhanced ICIC), and to further enhanced ICIC (feICIC). eICIC and feICIC use a technique known as ‘cell range expansion’(CRE) to increase the coverage area and reduce interference at the cell edge of the smaller cells. These techniques allow users to be offloaded from the macrocell to the small cell, and are especially important when carrier aggregation into being used. Testing a network employing eICIC/feICIC requires the tester to apply the relevant mobile device measurement procedures in order to feedback correct and reliable information to the network.

CoMP was introduced to further enhance LTE-A performance. HetNets often do not deliver the expected user experience, mainly because of poor cell-edge performance due to the lack of traffic coordination and interference management between small cells and macrocells. CoMP coordinates transmission and reception between different transmitting and receiving cells through the use of load balancing, coordinated scheduling, and the management of signal power and interference. The tight synchronization needed between multiple transmitting and receiving points means that CoMP is challenging both to configure and to validate. Using realistic CoMP usage scenarios in both uplink and downlink when testing enables operators and vendors to perform lab and field trials incorporating realistic performance tests, and thus maximize throughput in their HetNet deployments.

The demands are huge

So what are the main challenges for testing the new features, as each is agreed? Physical layer performance will become more difficult to validate for massive MIMO at higher carrier frequencies, and this is equally a problem that will need to be solved before 5G can be introduced. Another challenge will be testing the fusion of multiple technologies within one system. Not only do features need to be tested in isolation, but crucially where applicable along with the interaction between those, for example testing downlink CoMP in combination with carrier aggregation, and LAA alongside higher order MIMO schemes. As the demand on the networks increases, testing needs to take place for significantly larger numbers of UEs, in order to ensure that the system and user KPIs are met when the network is loaded. This is particularly challenging at the cell edge where interference is prominent.

From a network test point of view, it is crucial that support for new features – and the interaction between them – is made available for R&D as soon as possible; so that network performance can be validated under realistic user scenarios before the features are introduced on real mobile terminals. As capacity becomes an even greater challenge, intelligent debugging capabilities are being developed to validate the system performance and specific of the stack under high load conditions. However as feature interaction and capacity testing place ever increasing demands on validation, it is important to provide KPI metrics that do not create ‘information overload’, but instead genuinely benefit testers and help them to identify where there is a performance bottleneck.


 

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