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What is the Internet of Robotic Things all about?

9 Oct

Internet of Robotic Things, the confluence of the Internet of Things and robotics, is a concept where autonomous machines will gather data from multiple sensors (embedded and sourced) and communicate with each other to perform tasks involving critical thinking.

As the name implies, Internet of Robotic Things is the amalgamation of two cutting-edge technologies, the Internet of Things and Robotics. The vision behind this concept is to empower a robot with intelligence to execute critical tasks by itself. To comprehend this technology better, let’s first break it down to its components. The Internet of Things brings gives a digital heartbeat to physical objects.

And robotics is a branch of computer science and engineering that deals with machines that can work autonomously. And what actually happens when these two technologies unite? Internet of Robotic Things is a concept where IoT data helps machines interact with each other and take required actions. In simpler words, it refers to robots that communicate with other robots and take appropriate decisions on their own. Pervasive sensors, cameras, and actuators embedded in the surroundings and also self-help robots collect information in real-time.

Internet of Robotic Things : the importance

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Every business today is striving to gain a competitive edge in the market. And to achieve their set goals, leveraging the newest technologies is a must. Internet of Things and Robotics are two such technologies that have been known for their compelling use cases. And now, the IoT-robotics convergence promises to offer incredible applications to several industries. With the ability to get information from various sources and react accordingly, robots perform necessary functions without requiring human intervention. As a result, processes get streamlined and optimized. Consequently, businesses can seamlessly achieve work accuracy, productivity goals, and revenue benefits.

Internet of Robotic Things: the use cases

Internet of Robotic Things can be the perfect choice for industries that deal with heavy duty work or repetitive manual jobs. Let’s check out a few potential use cases through which industries can benefit from this newly emerged concept.

  • Robots at warehouses can inspect product quality, check for product damages, and also help with put-aways. Without humans playing any role, robots can analyze the surroundings with the IoT data and respond to situations as needed.
  • A robot can effectively play the role of a guidance officer and help customers with parking space availability. By checking the parking lots, robots can assist customers with the right place to park their vehicles.
  • Robots can automate the labor-intensive and life-threatening jobs at a construction site. Right from scaffolding to loading and unloading heavy construction equipment, robots can take care of every on-site task responsibly. With the help of intelligent robots, construction engineers and managers can ensure enhanced worker health and safety.

Realizing the importance and benefits of the Internet of Robotic Things, several forward-thinking companies are investing significantly in this technology. Industry behemoth, Amazon Robotics has deployed collaborative industrial robots to automate the activities in a warehouse fulfillment center. The MarketandMarkets report states the market of Internet of Robotic Things is expected to reach 21.44 billion US dollars by 2020. These numbers clearly reflect the promise of this technology,

Source: https://www.technologyforyou.org/what-is-the-internet-of-robotic-things-all-about/
09 10 19

Key Drivers and Research Challenges for 6G Ubiquitous Wireless Intelligence

25 Sep

The University of Oulu in Finland has published the world’s first white paper on 6G wireless technology. The white paper is titled ‘Key Drivers and Research Challenges for 6G Ubiquitous Wireless Intelligence’ and is based on information gathered at a summit of experts in the emerging 6G wireless capability sector held in Levi, Finnish Lapland, in March this year. It focuses on the key drivers and research priorities for the development of 6G technology, which the experts estimated would result in ‘ubiquitous wireless intelligence’ by 2030.

The paper consits of seven themes:

  • Social and business drivers of 6G wireless innovation, including adherence to the United Nations’ Sustainable Development Goals and the evolving needs of the data market: the paper notes that while the technical success of 5G has relied on new developments in many areas and will deliver a much wider range of data rates to a much broader variety of devices and users. 6G will require a substantially more holistic approach to identify future communication needs, embracing a much wider community to shape the requirements of 6G.
  • 6G use cases and new devices – the paper predicts a shift in user devices from smartphones toward wearable devices with virtual, augmented or mixed reality capability, along with the emergence of other innovations in technological engagement such as telepresence, mobile robots and autonomous vehicles; and identifies these as factors to be considered when constructing 6G-enabled networks;
  • Key performance indicators and projected spectrum capability for 6G wireless connectivity, which the experts say should aim to transmit at rates of up to 1Tbps per user;
  • Progress and challenges of the necessary radio hardware – communications applications and architecture must merge in order to offer the spectrum needed to achieve the requisite speeds for 6G connectivity;
  • Wireless systems and the physical layer of development – the paper highlights issues of increased energy consumption and data processing, saying: ‘Meeting all the challenging requirements identified requires a hyper-flexible network with configurable radios. AI and machine learning will be used in concert with radio sensing and positioning to learn about the static and dynamic components of the radio environment’;
  • 6G wireless networking, including secure privacy protection protocols and the growing role of Artificial Intelligence and blockchain capability; and
  • New service enablers – the paper highlights the growth of edge and cloud computing, machine learning and Artificial Intelligence and highlights the importance of shoring up privacy and trust in the network.

As 5G research is maturing and continues to support global standardization, we must start to start discussing what 6G can become and how to get there. Company representatives, researchers, decision-makers and other builders and members of smart society are invited to join this effort.

Click here to download the 6G White Paper on everything RF or  White paper 6G

5G: A Key Requirement for Autonomous Driving—Really?

25 Sep
With the first rollouts taking place around the world, many say the availability of 5G—along highways and in cities or ideally nationwide—is a precondition for self-driving cars. But is this really true?
Automotive examples tend to be front and center in global media coverage of planned 5G use cases, often with the claim that any country without 5G will fall behind when it comes to autonomous driving. But is mobile connectivity, in particular based on 5G, really required for autonomous driving, or will it simply play a supporting role? Let’s take a look at some specific use cases and the factors that could make them a reality.

Interacting with the Environment

As the automotive industry moves toward fully autonomous driving, the end goal is the literal meaning of the phrase: a car that can operate safely and independently of any human control. Such a vehicle must be able to detect any situation relevant to its driving, interpret that situation and any potential challenges, and then make a decision and take the most appropriate action. On first look, it seems clear that sending a car outside information such as road conditions in the near distance will enable it to surpass the capabilities of a human driver, who might not have such information. This could offer numerous benefits, such as preventing accidents, avoiding traffic jams, and creating safer and more efficient driving. However, when making critical decisions, an autonomous car should not be dependent on a component such as a mobile network, which is never 100 percent reliable.

Three categories of technologies are being discussed for cars to effectively interact with the surrounding environment (see figure 1):

Environment information capturing. Vehicles must be aware of their surroundings. They must use built-in cameras and sensors, such as radio detection and ranging (RADAR) and light detection and ranging (LIDAR) technology, which enable them to sense and interact with the world around them and build on the information available from maps and GPS. For example, to enable self-driving capabilities, Tesla equips each vehicle with eight cameras that provide 360-degree visibility and 12 ultrasonic sensors that detect objects. This number is likely to increase in the future.

Direct vehicle-to-everything (V2X) communication. Vehicles must communicate with each other and with roadside infrastructure. Despite all the latest developments, sensors are not perfect. Processing the wealth of information required for safe driving is complex, and ultimately, communication among human drivers (including non-verbal communications, such as hand signaling) must be fully mirrored in the future. Short-distance direct V2X communication is needed to communicate with other vehicles and nearby objects, including pedestrians and traffic lights—not only mirroring human activities but also going beyond what a driver can do.

Two V2X communication approaches are being pursued, with the 5.9 GHz spectrum being globally dedicated to this task:

  • Dedicated short-range communications (DSRC) in the United States and Intelligent Transport System G5 (ITS-G5) in Europe are based on Wi-Fi protocol 802.11p.
  • Cellular V2X technology (C-V2X) is a protocol that allows direct communication (not using mobile infrastructure). For now, it is based on LTE, but in the near future, it will be based on 5G standards.

Carrier-based V2X communication. Vehicles may also communicate over larger distances to send and receive more information. Even though short-range communication with connected infrastructure, such as beacons, could be used to transmit information to the car, some communication is likely to rely on mobile network infrastructure, also called C-V2X, but this time using a cellular network. Centrally collecting data from moving cars and providing aggregated information, including real-time maps, traffic data, road hazard warnings, and driving recommendations, will enhance cars’ safety levels and planning capabilities while also improving road usage efficiency through coordinated driving. In addition, vehicle-to-network (V2N) communication enables use cases that are not directly related to autonomous driving, including live function activation, preventive maintenance, and access to multimedia entertainment—all of which demand substantial bandwidth. However, capturing the benefits of carrier-based C-V2X will require a dense grid of mobile base stations.

Most original equipment manufacturers (OEMs) are already equipping their cars with a multitude of sensors to make them somewhat autonomous, including RADAR, LIDAR, and cameras. However, it’s not enough to enable safe driving at high or full automation (see figure 2). These technologies will need to be enhanced to achieve safety levels that approach or exceed those associated with human driving, and that is where communication comes into play.

Enabling Short-Range Communication

Safety-enhancing short-distance V2X communication is not yet broadly available in today’s communication standards or in vehicle installations. Political decision-makers are pushing an array of standards, including DSRC in the United States, ITS-G5 in Europe, and C-V2X in China. US automakers plan to implement DSRC in all new cars beginning in 2020, and China is pushing to establish 5G-based C-V2X. Europe recently fell short of endorsing ITS-G5 and is opting for a more technology-neutral approach, with all the consequences the lack of a standard is likely to entail.

To establish effective and reliable short-range communication among cars, two conditions must be in place regardless of which technology is used—and this is what car manufacturers, standard-setting bodies, and equipment manufacturers should focus on:

A common standard for direct vehicle-to-vehicle communication is needed—at least within major geographies. Standard-setting bodies and some large automakers, including Toyota, Renault, and Volkswagen, favor the standards of DSRC (in the United States) and ITS-G5 (in Europe) because of their technological maturity and lower manufacturing costs. Both standards are based on IEEE 802.11p and use similar hardware. These standards have evolved over the past 20 years and have been designed for the medium-range distance (300 meters to 1 kilometer), enabling communication among fast-moving objects and allowing for data rates of up to 25Mbps at minimal latencies. The C-V2X technology, which is based on mobile standards such as LTE today and 5G in the future, is much younger, and full standards and commercial deployment are not expected until 2020–2021. The most noticeable supporter for the new technology is the 5G Automotive Association, which is backed by several prominent car manufacturers, including BMW and Daimler, as well as equipment manufacturers such as Ericsson, Nokia, and Huawei; chip manufacturers such as Qualcomm; and major telecommunication operators such as Deutsche Telekom. Their reasons range from improved reliability, extended range (about twice as far), and cost efficiency, given the possibility to integrate C-V2X into the mobile communication modems already deployed in cars. At this point, it is not clear which standard will prevail. After a major lobbying battle, European policy makers have loosened their backing for ITS-G5 to avoid shutting out 5G-based C-V2X technologies and opening the door for forward-looking developments in European markets. However, the lack of an agreed-upon standard is hampering the second condition for establishing short-range communication among vehicles.

A critical mass of cars must be equipped with compatible short-range communication technologies to achieve the required network effects. Automotive OEMs will need to equip vehicles with these communication capabilities as soon as possible and configure them to send messages, such as the intention to change lanes, even though there is no one to receive the messages yet. Only by doing so can a critical mass be achieved to enable tomorrow’s autonomous vehicles to react to these messages—a classic network problem. The United States and China are establishing the required regulations for a standard communication technology, but Europe is still undecided about which, if any, technology to favor. Agreeing on a common standard would clearly benefit Europe. As time progresses, the time lag of standardization for C-V2X will become less of a problem, and coordinated adoption will quickly drive down unit costs for the associated chipsets for C-V2X once they are available. However, any extra cost from adding components to the car’s bill of material with no immediate benefit is not a compelling case for the automotive industry, which is already undergoing massive change. Therefore, even agreeing on a common standard might not be enough, and the industry might have to agree—or governments might have to enforce—that all cars are to be equipped with short-range communication. Only in this way can the inherent network problem be overcome.

Establishing Long-Range Communication

Because network- and carrier-based long-range C-V2X communication will help improve the safety of autonomous cars—although not a precondition to their existence—C-V2X’s primary requirement is the presence of a broadly established mobile network with the necessary capabilities. Generally, it is assumed that the latest technology network (5G) will be required. However, is this truly the case? The question is what type of information enables those enhanced levels of safety through C-V2X communication?

Various types of information must be brought to and from the car via long-range communication:

  • Non-time critical information into the car such as software and map updates (for example, coordinates of new construction sites) or from the car such as data captured by the car’s artificial intelligence (AI) unit (for example, improving the OEMs’ AI) or monitoring data, such as insurance information or the need for maintenance. Some of this information might be large, comparable to smartphone updates or even larger.
  • Time-critical information into the car such as urgent traffic alerts, crucial map updates, positioning corrections, directions for coordinated driving, and security-relevant information or information from the car, such as moving-car data (for example, for coordinated driving) or alerts, such as map updates and critical sensor data. This is mostly short messages with low latency requirements.
  • Communication and content such as video and audio streaming, web content, communication or messaging for entertainment, and information for work purposes—some of which require high bandwidth to function properly

Today’s LTE-based mobile networks could handle most of these use cases—assuming there is coverage in the areas where these cases are relevant and enough network capacity for the more bandwidth-hungry applications. Autonomous driving field tests, including on Germany’s highway A9, show that LTE networks—in combination with edge computing—can handle latency requirements of 15 milliseconds. Given that most time-critical applications had latency requirements of up to 100 milliseconds, this should be sufficient as a start to enable enhanced levels of safety.

Of course, 5G will have added benefits, especially additional network capacity, given the new frequency bands and higher spectral efficiency as well as ultra-low latency for short messages and the ability to more efficiently manage many connected objects, such as cars. However, beyond fulfilling the skyrocketing capacity needs for content, most of these benefits only come to fruition with a critical mass of autonomous cars, which is likely to be more than a decade away. Only then will coordinated driving become a reality, and it will require bidirectional ultra-low latency or massive car communication—mostly in areas with a high density of cars, such as highways and cities. The same is true for remote control and steering of driverless vehicles, which must overcome many other hurdles first, such as insurance and reliability, to become reality in broader environments. Consequently, the need for nationwide 5G coverage for the sake of autonomous driving is not foreseeable—although having it in the mix on highways and cities definitely helps.

5G’s Role in Enabling Autonomous Driving

So, is 5G truly required to enable autonomous driving? As discussed, in direct short-range V2X communication, 5G technology is a viable contender, and with China’s decision to back C-V2X and Europe’s openness, C-V2X might prevail even though alternatives do exist. In the short to mid-term, 5G in mobile networks does not appear to be essential to kick-start autonomous driving, contrary to many media assertions.

What’s more important is reliable mobile communication with extensive geographic—not just the population—coverage and sufficient capacity. The existing mobile networks—even if only based on 4G/LTE—can provide the basis for this if they are built out and if older technology is gradually replaced, re-farming the frequencies used by 3G and 2G. Clearly, 5G will supplement and enhance the networks, laying the path for the evolution of autonomous driving as other required technologies mature.

Much more essential for the rise of autonomous driving than a fast nationwide 5G rollout is that all stakeholders—automakers, chip and equipment manufacturers, industry bodies, regulators, and mobile operators—join forces to drive standards into the market. The automotive industry would be wise to learn an important lesson from the mobile industry: collaborating on standards is the primary driver for growth of network-based sectors in a fragmented, competitive landscape. The European success of the Global System for Mobile Communications (GSM) is a lighthouse example.

Source: https://www.atkearney.com/communications-media-technology/article/?/a/5g-a-key-requirement-for-autonomous-driving-really-
25 09 19

5G: Use it to leapfrog, others will be left behind

4 Aug

The most innovative sector, usually non-carrier related, must be supported by government. Cross-discipline talents are crucial…

The Philippines launched Southeast Asia’s beginnings of a commercial 5G service through a home broadband wireless connection in June 2019. The new service allows internet users connection speed of 20 Mbps to 100 Megabits per second (Mbps) through the 5G wireless network sans the trouble of time-consuming physical fiber optic connection underground. The new technology will speed up the adoption of broadband internet in the country and expedite the introduction of 5G wireless mobile communication in the 2020s.

Like other earlier generations of 1G to 4G mobile communication, the new 5G mobile communication system has the potential to drastically affect society through the new application areas developed along with the technology.

The table below shows how each successive generation of mobile communication has changed the world.

From the perspective of national development, the current transition from 4G to 5G is more significant than the earlier mobile communication generation shifts. While the technology behind 5G is essentially an engineering improvement over 4G, the application arena represents a revolution. The earlier 1G to 4G worked mainly on how to change and improve communications, and confined itself mostly to the consumer spaces in the economy. The critical application area in 5G will likely move to business and government space in the economy and holds significant promise to improve any countries’ productivity, regardless of whether they are developed or developing.
5G: Use it to leapfrog, others will be left behind 2

New use cases of 5G make it different 

Each generation of mobile communication encompasses all technologies of the previous generations and expands its economic footprint by embracing new activities as well as improving the old one. There are three new different use cases of the 5G network:

1. Enhanced mobile broadband (eMBB): High bandwidth internet access suitable for web browsing, video streaming and virtual reality. eMBB is the service just introduced in the Philippines via the 5G wireless broadband, and its full functionality will be utilized when mobile 5G smartphone service is introduced.

2. Massive machine type communication: This feature means we can install as many as a million monitoring devices in 1 square kilometer without physical wiring connection, and collect real-time data for analysis and action. This functionality means sensors can be monitoring everything anywhere in real-time.

3. Ultra-reliable low latency communication (URLLC): This means 5G system can receive and send back a signal from a faraway place in less than 10 milliseconds with an accuracy of 99.999 percent. This performance is better than the human response that runs into 50 to 100 milliseconds. URLLC allows remote control of many time-sensitive operations such as remote surgery, autonomous vehicle.

5G business model development and the critical role of government regulation

The three different use cases of 5G mean any operation that will benefit from more accurate real-time data collection, analysis and response is a candidate for productivity improvement using the technical capability of the 5G. There are many current government activities and business applications in developing countries that can tap the 5G platform and significantly promote economic development.

One prime candidate for using 5G platform is in real-time traffic management. The management system can use the Internet of Things (IoT) and low latency to build a connected traffic management infrastructure using the 5G platform to link all data collected by the various traffic monitoring sensors at appropriate control junctions. The data collected can then be processed by the artificial intelligence-based traffic management algorithms on the platform to issue real-time management instructions to direct and modify traffic at a particular traffic choke point.

5G: Use it to leapfrog, others will be left behind 3
The 5G technology opens the door of using the new communication technology to promote the growth of developing countries by boosting the productivity of existing economic activities. The opportunity can only be exploited by entrepreneurs who are also well versed in the details of the particular application domain. The country should take the initiative to foster the development of such entrepreneurship and help the entrepreneur to become the drivers in developing relevant business usage models for 5G.

One of the critical regulatory frameworks the government should provide is helping the non-carrier related entrepreneurs to tap the 5G network. For example, 5G network slicing allows operators to divide a single physical network — everything from the radio to the core network — into multiple virtual networks. Each network slice can have different speed limits, different latencies and different quality of service configuration. The charges levied by the carrier will materially affect the development of the use cases by the entrepreneurs. How to partition the revenue of different stakeholders through different fee structure is going to be a social issue for the government to resolve.

Another critical challenge to the government in using 5G to improve the economy is the reorientation of the country’s education setup. We noted in the case of traffic management: AI ability is a complementary competency if one wants to tap the potential of 5G. Hence the government should look at its education setup to develop more cross-discipline talents who can integrate the new technology with the requirement in the fields.

Source: https://www.manilatimes.net/5g-use-it-to-leapfrog-others-will-be-left-behind/594782/

5G use cases

10 Sep
With 5G promising “ultra-high throughput, ultra-low latency transmission, and edge computing”, Huawei and Softbank’s 5G use cases including real-time UHD video, robotic arm control and more.

Seeking their own slices of 5G supremacy, Japan’s Softbank Corp and the Japanese division of China’s Huawei Technologies have “jointly demonstrated various potential use cases for a 5G network.”

As can be seen by the two photos provided at the end of this article, the demonstration “included real-time UHD video transmission using ultra-high throughput, remote control of a robotic arm using ultra-low latency transmission and remote rendering via a GPU server using edge computing.”

In addition, the real-time UHD video transmission demonstrated throughput of “over 800 Mbps.”

The videos show a game of air Hockey being played, with a description of how this works in example 3, below.

The remote control of the robotic arm also demonstrated an “ultra-low latency one-way transmission of less than 2ms.”With SoftBank planning “various experiments to study 5G technologies and endeavouring to launch 5G commercial services around 2020,” it’s clear these kinds of demonstrations are just a glimpse into what is promised to be a glorious 5G future.

Of course, 5G promises to connect everyone to everything, everywhere, especially via a vast array of IoT devices, so security is still a major issue needing to be solved, but as with the final 5G standards, a lot of work is being done in all these regards to deliver solid solutions backed by superior security, and we’re just going to have to wait and see how successful the industry is at these issues.

As for the edge computing mentioned above, Huawei and Softbank state that, “in edge computing, servers are located near by base stations, i.e. at the edge of an mobile network, with a distributed way.”

The dynamic duo state that “This architecture allows us to realise ultra low latency transmission between the servers and mobile terminals. Also, it is possible to process a huge amount of data gathered by IoT devices to decrease the load of the mobile network.”

Here are the demonstration details provided by both companies, with accompanying infographics:

1. Real-time UHD video transmission

“A UHD camera was installed inside the demonstration room to capture outdoor scenery. The data from this camera was then compressed in real-time using an encoder and transmitted through the ultra-high throughput 5G network to a UHD monitor via a decoder, where the original data was recovered.

“In this demonstration, the scenery of the Odaiba Tokyo Bay area was successfully displayed on the UHD monitor using the ultra-high throughput provided by the 5G network. This technology can be applied to various industries, including tele-health or tele-education.”

Turn phone horizontal to see full image if viewing on mobile:

2. Immersive video

“Scenery was captured by a 180-degree camera equipped with four lenses pointing four different directions installed in the demonstration room, and captured scenery was distributed to smartphones and tablets over the 5G network.

“Four separate cameras were set up to capture the scenery in different directions, and the video images captured by these cameras were stitched together to generate a 180-degree panoramic video image that enabled multiple simultaneous camera views. Then the video image was compressed and distributed to smartphones or tablets in real-time over the 5G network, which gives users a truly realistic user experience.

“Coupled with a 5G network, this technology can be applied to virtual reality (VR) or augmented reality (AR).”

3. Remote control of robotic arm with ultra-low latency

“A robotic arm played an air hockey game against a human in this demonstration. A camera installed on top of the air hockey table detected the puck’s position to calculate its trajectory.

“The calculated result was then forwarded to the robotic arm control server to control the robotic arm. In this demonstration, the robotic arm was able to strike back the puck shot by the human player on various trajectories. This technology can be applied to factory automation, for example.”

4. Remote rendering by GPU server

“Rendering is a technology used to generate videos or images using computers with GPUs (Graphic Processor Unit). This technology is used for generating HD videos in computer games or for CAD (Computer Aided Design). The rendering consumes a large amount of computing resources. Therefore, HD computer games or HD CADs were not executable on tablets or smartphones on their own.

“However, edge computing technology provided by the 5G network allows us to enjoy HD computer games or HD CADs on tablets or smartphones. A GPU server located near a 5G base station performed rendering and the image generated by the GPU server was sent to the tablet over the ultra-high throughput and ultra-low latency 5G network. This technology can be applied to check the CAD data at a construction site with a tablet or to enjoy a HD game application on a smartphone.”

Huawei and Softbank note that: “Immersive video” and “remote control of a robotic arm with ultra-low latency” were jointly integrated and configured for demonstration by SoftBank and Huawei. “UHD real-time video transmission” and “Remote rendering with GPU servers” were integrated and configured for demonstration by SoftBank.

Here are the photos of the Air Hockey game in action:

 

5G use cases demonstrated by SoftBank and Huawei

Source: https://www.itwire.com/telecoms-and-nbn/79837-5g-use-cases-demonstrated-by-softbank-and-huawei.html

IoT Data Analytics

22 Aug

It is essential for companies to set up their business objectives and identify and prioritize specific IoT use cases

As IoT technologies attempt to live up to their promises to solve real-world problems and deliver consistent value for companies, there is still confusion among businesses on how to collect, store, and analyze a massive amount of IoT data generated from Internet-connected devices, both from industry and consumers, and unlock its value. Many businesses that are looking to collect and analyze IoT data are still unacquainted with the benefits and capabilities the IoT analytics technology offers, or struggle with how to analyze the data to continuously benefit their business in different ways such as cost reduction, improving product and services, safety and efficiency, and enhancing customer experience. Consequently, businesses still have the prospect of creating competitive advantage by mastering complex IoT technology and fully understanding the potential of IoT data analytics capabilities.

The Product Key Features and Factors to Consider in the Selection Process
To help businesses understand the real potential and value of IoT data and IoT analytics across various IoT analytics applications and guide them in the selection process, Camrosh and Ideya Ltd., published a joint report titled IoT Data Analytics Report 2016. The report examines the IoT data analytics landscape and discusses key product features and factors to consider when selecting an IoT analytics tool. Those include:

  1. Data sources (data types and formats analysed by IoT data analytics)
  2. Data preparation process (data quality, data profiling, Master Data Management (MDM), data virtualization and protocols for data collection)
  3. Data processing and storage (key technologies, data warehousing/vertical scale, horizontal data storage and scale, data streaming processing, data latency, cloud computing and query platforms)
  4. Data Analysis (technology and methods, intelligence deployment, types of analytics including descriptive, diagnostic, predictive, prescriptive, geospatial analytics and others)
  5. Data presentation (dashboard, data virtualization, reporting, and data alerts)
  6. Administration Management, Engagement/Action feature, Security and Reliability
  7. Integration and Development tools and customizations.

In addition, the report explains and discusses other key factors impacting the selection process such as scalability and flexibility of data analytics tools, vendor’s years in business, vendor’s industry focus, product use cases, pricing and key clients and provide a directory and comparison of 47 leading IoT data analytics products.

The Product Key Features and Factors Impacting the Selection Process

IoT vendors and products featured and profiled in the report range from large players, such as Accenture, AGT International, Cisco, IBM Watson, Intel, Microsoft, Oracle, HP Enterprise, PTC, SAP SE, Software AG, Splunk, and Teradata; midsize players, such as Actian, Aeris, Angoss, Bit Stew Systems, Blue Yonder, Datameer, DataStax, Datawatch, mnubo, Mongo DB, Predixion Software, RapidMiner, and Space Time Insight; as well emerging players, such asBright Wolf, Falkonry, Glassbeam, Keen IO, Measurence, Plat.One, Senswaves, Sight Machine, SpliceMachine, SQLStream, Stemys.io, Tellient, TempoIQ, Vitria Technology, waylay, and X15 Software.

Business Focus of Great Importance
In order to create real business value from the Internet of Things by leveraging IoT data analytics, it is essential for companies to set up their business objectives across the organization and identify and prioritize specific IoT use cases that support each of the organizational functions. Companies need to ask specific questions that need to be addressed (such as “How can we reduce cost?”, “How can we predict potential problems in operations before they happen?”, “Where and when are those problems most likely to occur?”, “How can we make a product smarter and improve customer experience?”, etc.) and identify which data and what type of analysis are needed to address these key questions.

For that reason, the report examines use cases of IoT data analytics across a range of business functions such as Marketing, Sales, Customer Services, Operations/Production, Services and Product Development, as well as illustrates use cases across industry verticals including Agriculture, Energy, Utilities, Environment & Public Safety, Healthcare/Medical & Lifestyle, Wearables, Insurance, Manufacturing, Military/Defence & Cyber Security, Oil & Gas, Retail, Public Sector (e.g., Smart Cities), Smart Homes/Smart Buildings, Supply Chain, Telecommunication and Transportation. To help companies get the most from their IoT deployments and select IoT data analytics based on industry specialization, the report addresses use cases for each of the mentioned industry sectors, its benefits, and indicates use cases covered by each of the featured IoT data analytics tools.

Selecting the right IoT analytics tool that fits the specific requirements and use cases of a business is a crucial strategic decision, because once adopted, IoT analytics impacts not only business processes and operations, but also the whole supply chain and people involved by changing the way information is used, and the overall impact it has on the organization. Furthermore, it is evident that companies that invest in IoT with a long-term view and business focus are well positioned to succeed in this fast evolving area.

Building the Right Partnerships – The Key to IoT Success
IoT data analytics vendors have created a broad range of partnerships and built an ecosystem to help businesses design and implement end-to-end IoT solutions. Through the detailed analysis and mapping of the partnerships formed by IoT analytics vendors, the IoT data analytics report shows that nearly all featured IoT analytics vendors reviewed are interconnected to one or more of the sample set, as well as a list of partners from different industries.

The report reveals that the partnerships play a key role in the ecosystem and enable vendors to address specific technology requirements, access market channels, and other aspects of providing services through partnering with enablers in the ecosystem. With the emergence of new use cases and their increasing sophistication, industry domain knowledge will increase in importance.

Partner Ecosystem Map of Featured IoT Analytics Vendors produced in NodeXL

Other factors, such as compatibility with legacy systems, capacity for responsive storage and computation power, as well as multiple analytics techniques and advanced analytics functions are increasingly becoming the norm. Having a good map to find one’s way through the dynamic and fast-moving IoT analytics vendors’ ecosystem is a good starting point to make better decisions when it comes to joining the IoT revolution and reaping its benefits.

Source: http://cloudcomputing.sys-con.com/node/3892716

If my mobile is camped to LTE & browsing the internet using LTE, Then I received a voice call. Will my data connection be terminated or will it be temporariy suspended?

19 Apr

Currently the LTE networks does not support the voice(circuit switched capabilities). There are certain features like CS Fallback or VoLTE that can be implemented to facilitate a voice call over the LTE network. If CS fall back feature is active in the network (considering the operator has 2G/3G or cdma network active) then the incoming voice call will be paged over LTE network and the voice call will be connected through the existing 2G/3G or CDMA network using the the extended service request commands. Now when you are on a voice call in 2G/3G or CDMA network then the already existing LTE data download will be stoped and a new data session will be created in the 2G/3G or CDMA network in continuation from the last LTE data download.
I hope this clarifies the doubt.

In case of LTE voice services are provided by integrating with IMS with LTE that is VoLTE. Voice calls are established using new bearer connection and data will packets running on different bearer connection, Hence both data and voice service co exists there will not be any disconnection.

 

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