A recent article published in IEEE Intelligent Systems highlights the requirements the Internet of Things (IoT) will place on search engines and brings together the latest research being carried out in this field.
‘On Searching the Internet of Things: Requirements and Challenges’ has been written by leading researchers working in the field of next generation communications at the University of Surrey’s Institute of Communication Systems (home of the 5G Innovation Centre) and Ohio Center of Excellence in Knowledge Enabled Computing (Kno.e.sis) at Wright State University (USA).
Experts in next generation communications outline how internet search mechanisms will need to change to support the Internet of Things (IoT) whereby billions of devices will become connected
Complex future technologies such as smart cities, autonomous cars and environmental monitoring will demand machine-to-machine searches that are automatically generated depending on location, preferences and local information
New requirements will include being able to access numerical and sensory data, and providing secure ways of accessing data without exposing the devices to hackers
An article highlighting the latest research in this area by academics at the University of Surrey and Wright State University (USA) has been published in IEEE Intelligent Systems
A recent article published in IEEE Intelligent Systems highlights the requirements the Internet of Things (IoT) will place on search engines and brings together the latest research being carried out in this field. ‘On Searching the Internet of Things: Requirements and Challenges’ has been written by leading researchers working in the field of next generation communications at the University of Surrey’s Institute of Communication Systems (home of the 5G Innovation Centre) and Ohio Center of Excellence in Knowledge Enabled Computing (Kno.e.sis) at Wright State University (USA).
With more and more IoT devices being connected to the internet, and smart city data projects starting to be implemented, there is an urgent need to develop new search solutions which will allow information from IoT sources to be found and extracted. While existing search engines have ever more sophisticated and effective ways of crawling through web pages and searching for textual data, the article argues that they will not be effective in accessing the type of numerical and sensory data which IoT devices will need to gather.
The article states that whereas in the past, human users have searched for information on the web, the IoT will see more machine-to-machine searches which are automatically generated depending on location, preferences and local information. Autonomous vehicles, for example, will need to automatically collect data (such as traffic and weather information) from various sources without a user being involved.
The IoT also presents a challenge in terms of cyber security. Applications which rely on public data, such as smart city technologies, need to be very accessible to make them available to a wide range of applications and services. Search mechanisms for these devices will need to provide efficient methods of indexing, crawling and finding data while ensuring the data is safe from hackers.
The University of Surrey’s 5G Innovation Centre – the UK’s largest hub for research into next generation communications– is conducting a number of projects in the field of IoT search engines. These include developing search mechanisms that describe the sources of the data required, and developing algorithms for clustering and analysis of IoT ‘time-series’ data.
The article’s lead author Dr Payam Barnaghi (a Reader in Machine Intelligence at the University of Surrey), says: “Search engines have come a long way since their original purpose of locating documents, but they still lack the connection between social, physical and cyber data which will be needed in the IoT era. IoT data retrieval will require efficient and scalable indexing and ranking mechanisms, and also integration between the services provided by smart devices and data discovery.
“IoT technologies such as autonomous cars, smart cities and environmental monitoring could have a very positive impact on millions of lives. Our goal is to consider the many complex requirements and develop solutions which will enable these exciting new technologies.”
The article’s second author, Professor Amit Sheth of Kno.e.sis, comments: “I see tremendous opportunities to effectively utilize physical (especially IoT), cyber and social data by improving the abilities of machines to convert diverse data into meaningful abstractions that matter to human experiences and decision making. IoT search, particularly for devices or machines to interact with each other to find and aggregate relevant information on a human’s behalf, will become a critical enabler.”
As an important step towards graphene integration in silicon photonics, researchers from the Graphene Flagship have published a paper which shows how graphene can provide a simple solution for silicon photodetection in the telecommunication wavelengths.
Published in Nano Letters, this exciting research is a collaboration between the University of Cambridge (UK), The Hebrew University (Israel) and Johns Hopkins University (USA).
The mission of the Graphene Flagship is to translate graphene out of the academic laboratory, through industry and into society. This broad and ambitious aim has been at the forefront of the choices made to direct the Flagship; it focuses on real problem areas where it can make a real difference such as in Optical Communications.
Optical Communications are increasingly important because they have the potential to solve one of the biggest problems of our information age: energy consumption. Almost everything we do in everyday life consumes information and all of this information is powered by energy. If we want more and more information, we need more and more energy. In the near future, the major consumers of data traffic will be machine-to-machine communication and the Internet of Things (IoT).
To enable the IoT and the level of information it requires, current silicon photonics has a problem: it needs ten times more energy than we can provide. So, if we want this new, improved internet age, new technological, power-efficient solutions need to be found. This is why the drive to graphene-based optical communication is so important.
Over the last few years, optical communications have increased their viability over standard metal-based electronic interconnects. The current silicon-based photodetector used in optical communications has a major issue when it comes to detecting data in the near infrared range, which is the range used for telecommunications. The telecom industry has overcome this problem by integrating germanium absorbers with the standard silicon photonic devices. They have been able to make fully functioning devices on chips using this process. However, this process is complex.
In the new paper, graphene is interfaced with silicon on chip to make high responsivity Schottky barrier photodetectors. These graphene-based photodetectors achieve 0.37A/W responsivity at 1.55μm using avalanche multiplication. This high responsivity is comparable to that of the Silicon Germanium detectors currently used in silicon photonics.
Prof. Andrea Ferrari from the Cambridge Graphene Centre, who is also the Science and Technology Officer and the Chair of the Management Panel for the Graphene Flagship stated; “This is a significant result which proves that graphene can compete with the current state of the art by producing devices that can be made more simply, cheaply and work at different wavelengths. Thus paving the way for graphene integrated silicon photonics.”
Researchers at Disney Research and ETH Zurich have demonstrated that consumer-grade light-emitting diode (LED) bulbs can, with some modifications, do double duty — both illuminating a room and providing a communications link for devices in that room.
This visible light communication (VLC) system would be suitable for connecting the many devices, such as appliances, wearable devices, sensors, toys and utilities, that could comprise the Internet of Things, or IoT, said Stefan Schmid, a Ph.D. student at Disney Research and ETH Zurich.
LEDs can both produce light and serve as light sensors. By having individual LEDs alternate between sending modulated light signals and serving as receivers of signals, it is possible to create a network of bulbs that can send messages to each other and connect to devices, while having no discernible effect on room lighting.
Schmid and his colleagues designed and implemented such a VLC system, demonstrating that it is a viable way to interconnect devices within a room.
North Star BlueScope Steel, a steel producer for global building and construction industries, today announced that it is applying IBM Watson Internet of Things (IoT) technology and wearable devices to pioneer novel approaches to help protect workers in extreme environments. The IBM Employee Wellness and Safety Solution, a research project that analyzes data collected from sensors in workers’ wearables, provides data to North Starmanagement in real time when the technology senses potentially problematic conditions.
Employees working in extreme environments face a daily risk from conditions that include everything from high heat and toxic gas to open flames and heavy-machinery accidents. Overexertion and falls account for more than $25 billion in U.S. workers’ compensation costs a year, according to the Liberty Mutual Research Institute 2014 Workplace Safety Index1, yet there is currently no practical way to verify that mandatory safety controls and personal protective equipment are being used in hazardous environments. In fact, nearly 3 million nonfatal occupational injuries were recorded in 20142.
“Our global economy relies on hundreds of millions of workers who do their jobs under extreme environmental conditions, and now we are exploring ways to apply the Internet of Things and cognitive computing to help organizations prevent accidents and to keep their employees safer,” said Harriet Green, general manager, IBM Watson IoT, Commerce and Education. “We use the IoT to gather, integrate and analyze sensor data from wearable devices. When coupled together with innovative cognitive capabilities and data from important external sources such as the environment and weather, it creates enormous potential for better managing health, wellness and safety to truly help transform the way these vital workers perform their jobs.”
The research group of Professor Hideo Ohno and Associate Professor Shunsuke Fukami of Tohoku University has demonstrated the sub-nanosecond operation of a nonvolatile magnetic memory device.
Recently, the concept of “Internet of Things” (IoT) – a giant network of connected devices, people and things – has been attracting a great deal of attention. Although its range of application is limited at this stage, it is expected that in the near future, IoT will be widely applied and will play important roles in fields such as security, automated driving, social infrastructure and disability aid.
An integrated circuit, or microcontroller unit, is the brain in the IoT society, where information is acquired, processed, and transmitted. Thus, development of device technologies to make integrated circuits ultralow-power and high-performance, or high-speed, is of great importance for the progress of the IoT society.
In terms of low-power, the use of nonvolatile memories is known to be effective.
On the other hand, in terms of high-performance, it has been difficult for the nonvolatile memories which are both currently available (commercialized) and under development (not commercialized yet) to achieve the speed comparable to the one realized with currently-used volatile static random access memories.
The research group at Tohoku University had previously announced that they had developed a new-structure nonvolatile magnetic memory device. The device has a three-terminal configuration, which is different from the two-terminal magnetic memory device that is just about to hit the market.
The “Internet of Things” could make cities “smarter” by connecting an extensive network of tiny communications devices to make life more efficient. But all these machines will require a lot of energy. Rather than adding to the global reliance on fossil fuels to power the network, researchers say they have a new solution.
Human voices are individually recognizable because they’re generated by the unique components of each person’s voice box, pharynx, esophagus and other physical structures.
Researchers are using the same principle to identify devices on electrical grid control networks, using their unique electronic “voices” – fingerprints produced by the devices’ individual physical characteristics – to determine which signals are legitimate and which signals might be from attackers. A similar approach could also be used to protect networked industrial control systems in oil and gas refineries, manufacturing facilities, wastewater treatment plants and other critical industrial systems.
The research, reported February 23 at the Network and Distributed System Security Symposium in San Diego, was supported in part by the National Science Foundation (NSF). While device fingerprinting isn’t a complete solution in itself, the technique could help address the unique security challenges of the electrical grid and other cyber-physical systems. The approach has been successfully tested in two electrical substations.
“We have developed fingerprinting techniques that work together to protect various operations of the power grid to prevent or minimize spoofing of packets that could be injected to produce false data or false control commands into the system,” said Raheem Beyah, an associate professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. “This is the first technique that can passively fingerprint different devices that are part of critical infrastructure networks. We believe it can be used to significantly improve the security of the grid and other networks.”
The networked systems controlling the U.S. electrical grid and other industrial systems often lack the ability to run modern encryption and authentication systems, and the legacy systems connected to them were never designed for networked security. Because they are distributed around the country, often in remote areas, the systems are also difficult to update using the “patching” techniques common in computer networks. And on the electric grid, keeping the power on is a priority, so security can’t cause delays or shutdowns.
“The stakes are extremely high, but the systems are very different from home or office computer networks,” said Beyah. “It is critical that we secure these systems against attackers who may introduce false data or issue malicious commands.”
Beyah, his students, and colleagues in Georgia Tech’s George W. Woodruff School of Mechanical Engineering set out to develop security techniques that take advantage of the unique physical properties of the grid and the consistent type of operations that take place there.
For instance, control devices used in the power grid produce signals that are distinctive because of their unique physical configurations and compositions. Security devices listening to signals traversing the grid’s control systems can differentiate between these legitimate devices and signals produced by equipment that’s not part of the system.
Another aspect of the work takes advantage of simple physics. Devices such as circuit breakers and electrical protection systems can be told to open or close remotely, and they then report on the actions they’ve taken. The time required to open a breaker or a valve is determined by the physical properties of the device. If an acknowledgement arrives too soon after the command is issued – less time than it would take for a breaker or valve to open, for instance – the security system could suspect spoofing, Beyah explained.
To develop the device fingerprints, the researchers, including mechanical engineering assistant professor Jonathan Rogers, have built computer models of utility grid devices to understand how they operate. Information to build the models came from “black box” techniques – watching the information that goes into and out of the system – and “white box” techniques that utilize schematics or physical access to the systems.
“Device fingerprinting is a unique signature that indicates the identity of a specific device, or device type, or an action associated with that device type,” Beyah explained. “We can use physics and mathematics to analyze and build a model using first principles based on the devices themselves. Schematics and specifications allow us to determine how the devices are actually operating.”
The researchers have demonstrated the technique on two electrical substations, and plan to continue refining it until it becomes close to 100 percent accurate. Their current technique addresses the protocol used for more than half of the devices on the electrical grid, and future work will include examining application of the method to other protocols.
Because they also include devices with measurable physical properties, Beyah believes the approach could have broad application to securing industrial control systems used in manufacturing, oil and gas refining, wastewater treatment and other industries. Beyond industrial controls, the principle could also apply to the Internet of Things (IoT), where the devices being controlled have specific signatures related to switching them on and off.
“All of these IoT devices will be doing physical things, such as turning your air-conditioning on or off,” Beyah said. “There will be a physical action occurring, which is similar to what we have studied with valves and actuators.”
MIT researchers have developed a new chip designed to implement neural networks. It is 10 times as efficient as a mobile GPU, so it could enable mobile devices to run powerful artificial-intelligence algorithms locally, rather than uploading data to the Internet for processing.
In recent years, some of the most exciting advances in artificial intelligence have come courtesy of convolutional neural networks, large virtual networks of simple information-processing units, which are loosely modeled on the anatomy of the human brain. Neural networks are typically implemented using graphics processing units (GPUs), special-purpose graphics chips found in all computing devices with screens. A mobile GPU, of the type found in a cell phone, might have almost 200 cores, or processing units, making it well suited to simulating a network of distributed processors.
Versatile chip also offers multiple applications in various electronic devices
Scientists at Nanyang Technological University, Singapore (NTU Singapore) have developed a small smart chip that can be paired with neural implants for efficient wireless transmission of brain signals.
Neural implants when embedded in the brain can alleviate the debilitating symptoms of Parkinson’s disease or give paraplegic people the ability to move their prosthetic limbs.
However, they need to be connected by wires to an external device outside the body. For a prosthetic patient, the neural implant is connected to a computer that decodes the brain signals so the artificial limb can move.
These external wires are not only cumbersome but the permanent openings which allow the wires into the brain increases the risk of infections.
The new chip by NTU scientists can allow the transmission of brain data wirelessly and with high accuracy.
Assistant Professor Arindam Basu from NTU’s School of Electrical and Electronic Engineering said the research team have tested the chip on data recorded from animal models, which showed that it could decode the brain’s signal to the hand and fingers with 95 per cent accuracy.
“What we have developed is a very versatile smart chip that can process data, analyse patterns and spot the difference,” explained Prof Basu.
“It is about a hundred times more efficient than current processing chips on the market. It will lead to more compact medical wearable devices, such as portable ECG monitoring devices and neural implants, since we no longer need large batteries to power them.”
Different from other wireless implants
To achieve high accuracy in decoding brain signals, implants require thousands of channels of raw data. To wirelessly transmit this large amount of data, more power is also needed which means either bigger batteries or more frequent recharging.
This is not feasible as there is limited space in the brain for implants while frequent recharging means the implants cannot be used for long-term recording of signals.
Current wireless implant prototypes thus suffer from a lack of accuracy as they lack the bandwidth to send out thousands of channels of raw data.
Instead of enlarging the power source to support the transmission of raw data, Asst Prof Basu tried to reduce the amount of data that needs to be transmitted.
Designed to be extremely power-efficient, NTU’s patented smart chip will analyse and decode the thousands of signals from the neural implants in the brain, before compressing the results and sending it wirelessly to a small external receiver.
This invention and its findings were published last month in the prestigious journal, IEEE Transactions on Biomedical Circuits & Systems, by the Institute of Electrical and Electronics Engineers, the world’s largest professional association for the advancement of technology.
Its underlying science was also featured in three international engineering conferences (two in Atlanta, USA and one in China) over the last three months.
Versatile smart chip with multiple uses
This new smart chip is designed to analyse data patterns and spot any abnormal or unusual patterns.
For example, in a remote video camera, the chip can be programmed to send a video back to the servers only when a specific type of car or something out of the ordinary is detected, such as an intruder.
This would be extremely beneficial for the Internet of Things (IOT), where every electrical and electronic device is connected to the Internet through a smart chip.
With a report by marketing research firm Gartner Inc predicting that 6.4 billion smart devices and appliances will be connected to the Internet by 2016, and will rise to 20.8 billion devices by 2020, reducing network traffic will be a priority for most companies.
Using NTU’s new chip, the devices can process and analyse the data on site, before sending back important details in a compressed package, instead of sending the whole data stream. This will reduce data usage by over a thousand times.
Asst Prof Basu is now in talks with Singapore Technologies Electronics Limited to adapt his smart chip that can significantly reduce power consumption and the amount of data transmitted by battery-operated remote sensors, such as video cameras.
The team is also looking to expand the applications of the chip into commercial products, such as to customise it for smart home sensor networks, in collaboration with a local electronics company.
Southampton researchers compared four Internet of Things interaction techniques for the configuration of IoT devices, looking for methods that allowed security, but were quick and easy to use.
Two of the techniques used a more ‘traditional’ approach by connecting the smartphone and the IoT device through a USB or audio cable, via the smartphone’s headphone socket.
The third technique used a ‘Wi-Fi-only approach, where the smartphone creates a special temporary Wi-Fi network, or ‘ad-hoc network’, to which the IoT device automatically connects before being redirected to the correct permanent network.
The final option was the smartphone and the IoT device exchanging information through light: the smartphone’s screen flashed black and white to mean binary ‘zero’ or ‘one’; the IoT device read this light/binary pattern to learn the password from the smartphone.
Carnegie Mellon University will turn its campus into a living laboratory for a Google-funded, multi-university expedition to create a robust platform that will enable Internet-connected sensors, gadgets and buildings to communicate with each other.
“The goal of our project will be nothing less than to radically enhance human-to-human and human-to-computer interaction through a large-scale deployment of the Internet of Things (IoT) that ensures privacy, accommodates new features over time and enables people to readily design applications for their own use,” said Anind K. Dey, lead investigator of the expedition and director of CMU’s Human-Computer Interaction Institute.
Just as Carnegie Mellon pioneered distributed computing in the 1980s by deploying the first fully wired university campus, the expedition will use the CMU campus to develop and test the new IoT technologies.
Carnegie Mellon researchers will work with colleagues at Cornell, Stanford, Illinois and Google to create GIoTTO, a new platform to support IoT applications. Initial plans for GIoTTO include sensors that are inexpensive and easy to deploy, new middleware to facilitate app development and manage privacy and security, and new tools that enable end users to develop their own IoT experiences.
Lancaster University is about to take the concept of smart cities out of town. Computer scientists at Lancaster University are investigating how the Internet of Things could work in the countryside.
The Internet of Things – which enables object-to-object communication over the internet and real time data monitoring – has typically been associated with urban environments and until now the countryside has been left out in the cold.
Computer scientist Professor Gordon Blair of Lancaster University has won £171,495 from the Engineering and Physical Sciences Research Council to lead a new project in Conwy, North Wales, which will investigate how the Internet of Things could work in the countryside.
Working with partners at the Centre for Ecology and Hydrology, The British Geological Survey and Bangor University, the project launched on December 1 and will run for 18 months.
Problems from flooding and agricultural pollution to animal movements and drought could all potentially benefit from smart technology in the sticks.
The Internet of Things, which takes everyday objects and hooks them up to the internet, represents a shift in the way we gather and engage with information. Applying this booming technology to the countryside presents challenges – for example how to build a network when there are mountains and trees in the way – but researchers believe the benefits could be huge.
Sheep with digital collars, sensors on riverbanks, rainfall and river flow monitors could all soon form part of the project.
Take me to the story: Move over smart cities – the Internet of Things is off to the country