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2020 via time machine: networks and systems

When IoTs Become BOTs, The Dark Side of Connectedness

Edit Note : This is the second of a two-part series on this event. The first post can be read here.

Last week’s IEEE Technology Time Machine Symposium brought together leading academics, engineers, executives, and government officials from around the world, to engage in presentations and dialogue regarding the evolution of technology over the next decade. In yesterday’s post, I reviewed some of the insights regarding devices and technologies. Today, we’ll address networks and larger-scale systems such as smart grids.


Wireless continues to get better, with more bandwidth in more places. LTE offers a several-fold improvement over HSPA or HSPA+ in data rates as well as a ten-fold reduction in latency. However, operator executives such as Telstra CTO Dr. Hugh Bradlow and NTT Docomo VP Dr. Minoru Etoh pointed out that peak bandwidth is what customers tend to focus on, but total network capacity is the main challenge in providing an excellent customer experience: it’s nice to own a Lamborghini, but won’t get your there any faster at rush hour.

A single user may easily be able to get an HD video stream wirelessly over LTE, but Telstra studies have shown that only a few dozen end-users of a base station can do that simultaneously: due to LTE sector throughput limitations under good conditions. Moreover, this is not some temporary technology glitch or fault of underinvestment, but a challenging limit due to usable frequencies based on radio signal propagation characteristics and information theory.

This insight calls into question the approach being proposed where millions or billions of very “dumb” thin-client devices are wirelessly linked to entertainment and intelligence in the cloud. For devices, networks, and the cloud to function effectively at scale, smart trade-offs will need to be made in real time between when to render computationally challenging scenes in the cloud and send the scene over the network, and when to send raw information over the network for local rendering. Operators will also have to figure out how to manage priorities across users. Consequently, Bradlow sees intelligent traffic management as the key challenge of emerging wireless networks.

On the other hand, putting more cells with a smaller coverage radius could work, such as femtocells or even using Wi-Fi, but this means more wired networks to backhaul the traffic, reducing some of the ease-of-deployment benefits of wireless networks. Prof. Hequan Wu, former vice-chairman of the Chinese Academy of Engineering, pointed out that China Unicom’s (s chu) mobile data traffic had recently grown 62 percent. In a single quarter. China Mobile’s (s chl) grew 10 times its previous rate — in a single year. Mobile video is the challenge to solve, everything else is just rounding error.

For the Shanghai World Expo 2010, 10,000 mobile video cameras were installed on trucks and buses for security purposes. Consider the future hurdle of every passenger car sending or receiving several mobile video streams, as each passenger streams an on-demand movie or participates in a video conference. Moreover, Wu said that in some large Chinese cities, densities were up to 140,000 users per square kilometer.

HP’s (s hpq) Dr. Peter Hartwell dove into sensor networks, pointing out that the Internet of Things becomes really useful when dynamic data is used for real-time decision-making. A broad variety of sensors (temperature, humidity, power use) will all be integrated with processing and wireless connectivity into a single chip, enabling new applications, ranging from eHealth to smart grids. Hartwell pointed out that, as with cell phones, size will shrink and features will multiply. A variety of technologies are being incorporated here, such as “energy harvesting” to scavenge power from the environment, e.g., from vibration.

Putting it all together.

While the status and trends of many point technologies was addressed in depth, the consistent theme running through the conference might be said to be a more intelligent world, based on more information from more devices being used in real time to optimize the human experience while enhancing efficiency and environmental sustainability. Nokia (s nok) Services EVP Dr. Tero Ojanpera stated that anonymized, real-time data from mobile devices is the “ultimate collective intelligence,” enabling everything from optical vehicular traffic routing to locating a popular restaurant to creation of accurate maps. George Arnold, national coordinator for smart grid interoperability at NIST, observed that smart grid efforts will turn the traditional approach of building capacity to meet demand on its head, focusing instead on shaping demand to fit within capacity. Light bulbs with embedded Wi-Fi chips will be able to not only report that they are on, but reduce their output when the power infrastructure is stressed. And, the smart grid approach — which Arnold observed is the use of IT and communications technologies for utilities — isn’t limited to just electricity, but is also being applied to other utilities such as water and natural gas.

Telecom Italia’s (s ti) Roberto Saracco described the potential of a “mirror world,” a virtual world that is not just a play world in another galaxy or for social networking, but an exact virtual duplicate of the real-world populated with data from a variety of sensors. Such an environment might mean that by the time this conference is held in 2020, everyone will have the opportunity for face-to-face interaction—without having to physically travel to Hong Kong, or wherever, and the ability to shake hands—remotely, via haptic interfaces.

A hopeful, positive attitude was pervasive at the event, with NEC’s President Dr. Nobuhiro Endo outlining a strategy and future which is “friendlier to people, and friendlier to the planet.” Pervasive information and insight, emerging technologies, crowd-sourced intelligence, cloud-based global optimization, greener approaches, reduced power, and ease of use through natural interfaces may yet help solve some of the problems facing the world today.

Joe Weinman leads Communications, Media, and Entertainment Industry Solutions for Hewlett-Packard. The views expressed herein are his own.


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 The State of Data Innovation in the EU

by and October 9, 2017

Data innovation—the innovative use of data to create social and economic benefits—is making a significant mark in Europe. In economic terms, data innovation contributed about €300 billion to Europe’s economy in 2016 (or approximately 2 percent of GDP), and its value will likely more than double by 2020. Across society, data innovation is creating more responsive governments, better health care, and safer cities. But EU nations differ in the degree to which they are harnessing the benefits of data. This report uses a variety of indicators to rank EU member states and discusses why some countries are ahead and what others can do to catch up.

Download the full report (PDF).

Data innovation is happening today because the rapid growth in the ability to collect, store, analyze, and share large quantities of information at low cost drives new forms of economic activity, scientific discovery, and social innovation. For example, in health care, greater use of medical data can help doctors to diagnose problems much earlier, and manage long-term conditions better. In schools, teachers and administrators can use data to personalize educational software to meet the needs of individual pupils. And in business, an array of data-driven tools can help companies streamline their business processes and become more responsive to their customers. In the financial sector, for example, companies use sophisticated analytics and large datasets to prevent fraud as well as to improve and expand their lending services.

Member states that more effectively embraced data innovation will find it easier to respond to social and economic challenges in the years ahead. This means member states that may lag behind other European countries today could lead the EU’s competitive edge in the future if they support and invest in the underpinnings of the data economy.

To identify the areas where member states are doing well or need to improve, this report examines a range of indicators across three categories:

  • Data: The availability of useable data and the effectiveness of government policies in promoting the supply and reuse of data. This includes the size of the national data economy, data sharing in health care, the extent and impact of open-data policies, and the robustness of freedom-of-information laws.
  • Technology: The availability and use of key digital infrastructure and systems, such as the Internet of Things, e-government, and high-speed broadband.
  • People and Firms: The use of data-driven technologies in the workplace, the prevalence of digital skills, and the role of education and civil society in developing such skills.

The report concludes with recommendations for policymakers on how to improve their country’s performance in data innovation. To summarize, governments need to prioritize three goals:

  1. Maximize the supply of reusable data. Governments should both avoid laws and regulations that stifle the supply and flow of data, such as overly burdensome data-protection rules and data-localization policies in different member states, and increase the supply of data, such as via open data and freedom-of-information policies.
  2. Improve infrastructure that supports data innovation. Governments should encourage the development of key technological platforms that enable data innovation, such as broadband, digital public services, smart meters, and smart cities.
  3. Develop data-science and data-literacy skills in workers. Governments should encourage the development of data-related skills through the education system and through professional training programs.

Overall Scores: Map and Rankings

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