Information Technologies (IT)

Technology topic

Information Technologies (IT)

Information technology is increasingly impacting almost every aspect of our lives, from communicating with friends and family to manufacturing of the products we use, the efficient supply of food, the provision of healthcare services, and the performance of financial markets and our nation’s economy.

The past decade has seen explosive growth in the generation of data and the creation of usable information from that data. This growth is expected to accelerate into the foreseeable future, fueled in part by the increasing interconnectedness of the products and services that we use.

This topic encourages the submission of proposals that present ground-breaking innovations in the generation, analysis, use, transmission or protection of information, where such innovations offer the potential for substantial commercial returns and a positive impact on society and the world in which we live. The subtopics below provide specific examples of technologies and applications, although given the enormous range and diversity in the field of IT these examples are inevitably incomplete. Proposals are encouraged under any of the specific subtopics IT1 to IT13. Proposals that do not fit these subtopics can be submitted under the subtopic “IT14: Other”

IT1. Artificial Intelligence; Machine Learning; Natural Language Processing

This subtopic focuses on information technology innovations in the field of artificial intelligence (AI), which refers to intelligence exhibited by machines or software. AI is usually limited or targeted in nature, with general machine-based intelligence remaining an elusive long-term goal.

Included in this subtopic are the technical sub-specialties of machine learning and natural language processing (NLP), both of which are disciplines within the broader field of artificial intelligence. Machine learning refers to processes in which an automated system can learn from data, rather than following a pre-specified set of rules, and in many cases can predict outcomes relating to the learned process. The aim of NLP is to extract information or derive meaning from human language (written or spoken) or to generate human language.

There are many technical approaches to AI, and an even greater diversity of potential applications. Examples of relevant technical fields include (but are not limited to): deep learning; artificial neural networks of various types; supervised, semi-supervised and unsupervised machine learning; machine learning algorithms; pattern recognition; image recognition; machine vision; fuzzy logic; uncertain reasoning using probabilistic methods; named entity recognition; sentiment analysis; natural language understanding; natural language generation; automatic summarization; language translation; analysis of structured or unstructured text; speech recognition; speech analysis; speech processing.

Applications of AI include (but are not limited to): robotics, including in automated manufacturing; industrial controllers; self-driving cars; analysis of online commentary; stock market analysis; optimization of finance operations and stock investments; analysis of medical records; clinical decision support systems for medical diagnosis; automated interpretation of medical test data (e.g. ultrasound scan data); cybersecurity; intrusion detection - in software systems, communications networks and sensor systems; fraud detection; cyber-physical control systems; improvements in human-computer interaction; automated document classification, indexing and retrieval; customer recommendation systems; personalization of customer services; intelligent virtual assistants; search engines, including image-based search; translation services (including speech-to-speech translation).

IT2. Image and Video

This subtopic focuses on information technology innovations that enhance the acquisition, processing, interpretation and use of images or video. This includes both innovations in human perception and use of images or video, and innovations in machine vision. The terms “image” and “video” should be interpreted in their broadest sense - image or video simply refers to static or time-varying data (respectively) that are representative of certain properties of the subject and that may be acquired optically or via ultrasound, X-ray, MRI, PET, or any other measurement technique. Applications are many and varied, ranging from cell-phone based 3D modeling to medical image processing for improved diagnostic accuracy and enhancements for robotic manufacturing systems. Deployment platforms may range from mobile devices (cell phones and tablets) to industrial settings (manufacturing plants).

Examples of relevant technical fields include (but are not limited to): automated image/video indexing and retrieval; object recognition; pattern recognition; facial recognition; recognition of human actions and behavior (e.g., in video surveillance applications); automated video categorization; video summarization; generation and manipulation of 3D models; image/video enhancement; image/video feature extraction and identification.

Many innovations in image and video processing rely on underlying methods developed more broadly in the field of artificial intelligence. Innovations employing artificial intelligence technologies should be submitted to this subtopic if they are primarily aimed at image or video based applications.

IT3. Quantum Information Technologies

This subtopic focuses on innovations in information and communications technologies that rely fundamentally on quantum mechanical properties and interactions. Typically such technologies generate, detect or manipulate quantum states in order to provide faster, more efficient or more secure information processing and communications.

Included in this subtopic are innovations at the component, sub-system and system level that result in substantial and usable improvements in the generation, transmission, detection, storage or processing of information, or the security and privacy of information.

Proposed innovations must offer the potential for robustness, reliability and scalability, with operation at or near room temperature being a feasible objective. Components and sub-systems should aim for compactness and energy efficiency, consistent with the requirements of the intended application.

Innovations that involve quantum communications over significant distances should preferably be deployable in current fiber-optic infrastructure or using current optical fiber technology.

Examples of relevant technical fields include (but are not limited to): single photon sources and detectors; generation, transmission and detection of qubits; entangled photon sources; generation, manipulation and detection of entangled qubits; quantum repeaters; quantum memories; quantum frequency conversion (e.g. to telecoms wavelengths); superdense coding; quantum error correction; quantum information processing; quantum algorithms. This subtopic covers a wide range of technical sub-specialties, and these examples are intended only to be indicative.

Examples of relevant areas of application include (but are not limited to): quantum key distribution; quantum cryptography; quantum communications links and networks; network-based authentication; quantum computing.

Proposals submitted to this subtopic must be aimed ultimately at commercialization, and should address the likely timeline to develop a minimum viable product or service. Proposals should address practical problems - such as, for example, the efficient and reliable coupling of single photon sources to optical fibers - that will need to be overcome in order for the proposed innovation to be commercially feasible. IT4. Cybersecurity; Authentication; Privacy This subtopic is intended to cover the major aspects of security related to the internet (except for Internet of Things cybersecurity, which is covered under subtopic IT5).

Cybersecurity refers to security applied both to the internet (including servers and connected devices) and to data stored in or transmitted over the internet. Generally this refers to security against malicious attacks rather than security against (for example) inadvertent data leakage. Cybersecurity is growing in importance due to a confluence of factors, including (i) increased use of the internet to monitor and control critical infrastructure, (ii) increased incidence of cyber-attacks against government and major institutions, (iii) the growing reliance by the general public on internet-based services.

Authentication refers to the reliable authentication of persons using the internet and devices connected to the internet, while privacy refers to the protection against compromise of personal information and user data.

Examples of relevant technical fields include (but are not limited to): detection of cyber vulnerabilities - for example, related to critical infrastructure or financial networks; detection and prevention of cyber-attacks; human factors analytics - to assess people risk; mobile device security; device-cloud security infrastructure; cloud computing security; security/privacy policy compliance; security for BYOD (bring-your-own device) and BYOC (bring-your-own-cloud); big data security; data loss prevention; information assurance; data integrity; encryption; key generation, key management and key distribution; access authorization; identity management; personal authentication - biometrics, multi-factor authentication.

IT5. Cybersecurity for the Internet of Things

The Internet of Things (IoT) is widely touted as the next wave of internet expansion, connecting embedded sensing and control electronics in everyday products ranging from cars to refrigerators, televisions, wearable electronics and other smart objects, as well as enabling new system visibility and control in industrial applications such as utility grids (the so-called “smart grid”) and improved healthcare through smart health applications (e.g., heart monitoring implants and implanted continuous glucose monitoring sensors). ABI Research estimates that the number of active connected devices will exceed 40 billion by 2020, more than double the estimated number in 2014, with roughly 75% of the growth coming from sensor nodes and other network-edge devices - i.e., IoT devices. Each IoT device provides an access point to the internet and therefore also offers an opportunity for cyber-attack. Currently most IoT devices incorporate little or no security, which combined with their increasing ubiquity presents an alarming scenario for future internet security, particularly because IoT devices are expected to influence or even control many aspects of our lives.

Most IoT devices operate in resource constrained environments. Usually they are subject to severe energy usage limits, with low bandwidth (and sometimes sporadic) communications to the internet, limited computing power and little on-board data storage. These characteristics present unique operational challenges and also unique challenges in providing an effective defense against cyber-attacks.

This subtopic calls for new and innovative approaches to providing cybersecurity for IoT systems. Proposed solutions should not be limited to conventional cybersecurity techniques - the unique characteristics of IoT systems are likely to require new and unconventional cybersecurity methods. Proposing companies are encouraged to think outside the box.

Note: This subtopic is focused on cybersecurity innovations pertaining to IoT. Hardware innovations related to IoT should be submitted to the Internet of Things (I) topic. IT6. Networking Technology This subtopic focuses on information technology innovations that will enhance the performance, functionality and monitoring of information networks, with particular emphasis on the internet and Internet of Things (IoT) networks.

Examples of relevant technical fields include (but are not limited to): software-defined infrastructure - including software defined networking and software defined storage; software-defined data centers; analytics to optimize network performance; network visualization; network protocols; technologies to reduce network congestion and improve network resiliency; network-based data storage and retrieval technologies; anywhere/anytime access to data and services; agile networking; machine-to-machine networking; peer-to-peer device networking; networking technologies for resource-constrained sensor-dense environments such as in IoT applications.

Note: This subtopic includes IT-based innovations pertaining to IoT networking technology. Hardware innovations related to IoT should be submitted to the Internet of Things (I) topic.

IT7. Mobile Computing; Internet of Things

This subtopic focuses on information technology innovations that will improve the performance or functionality of mobile devices and devices that operate in resource-constrained environments - such as in Internet of Things (IoT) applications. While there is some overlap with other subtopics, proposals submitted to this subtopic should be focused on innovations specifically intended for these platforms.

Examples of relevant technical fields include (but are not limited to): location technology; image recognition and processing; video processing; speech recognition and generation; translation services; improved human to mobile device interfaces; gesture and expression recognition and processing; bio-signal processing; crowdsourced storage; crowdsourced processing; device-cloud architecture; context-relevant analytics and services - i.e., involving situational and environmental information; data analytics and data processing to facilitate the Internet of Things; vehicle-based computing platforms.

Note: This subtopic includes IT-based innovations pertaining to IoT devices. Hardware innovations related to IoT should be submitted to the Internet of Things (I) topic.

IT8. Cloud Computing; High-Performance Computing

Cloud computing is characterized by the allocation of internet-based distributed computing resources on an as-needed basis across a shared platform. Multiple computing cores may be dedicated in parallel to achieve the required computing performance levels for a specific task. Similarly, high performance computing usually relies on the use of a large number of co-located or distributed cores running in parallel. To achieve the highest levels of performance, massively parallel supercomputers may employ many thousands of cores.

This subtopic focuses on innovations that result in substantial improvements to cloud computing or high performance computing platforms. These improvements may be in terms of computing power, computing efficiency, energy management, network storage requirements, the use of hybrid clouds, latency, data integrity and availability, cost, or any other factor of importance in such platforms, and may result from software- or hardware-based innovations. Included in this subtopic are innovations that will enable continued improvement in the performance of HPC platforms in the so-called post- Moore’s Law era.

Examples of applications that typically require the levels of computing power available through cloud computing or high performance computing include (but are not limited to): stock market analysis and prediction; cryptanalysis; weather forecasting; fluid dynamic modelling, acoustic modelling and other computationally intensive engineering modelling; advanced audio and video signal processing.

IT9. Cloud-based IT Services

This subtopic focuses on innovations that enable the provision of new or improved cloud-based IT services to address issues of commercial and societal importance. Such services may be directed primarily to businesses or consumers. Examples include (but are not limited to): processing of medical data such as X-ray, ultrasound, MRI or CT scans; business data analytics; sentiment analysis; analysis of financial documents; customized alerts regarding news events or stock market announcements; translation services; document indexing and retrieval; computing services; data storage services; location-based services; retail recommendations.

IT10. Big Data; Advanced Data Analytics

This subtopic focuses on information technology innovations in the fields of big data and advanced data analytics. These fields cover a wide range of technical sub-specialties and applications, and the examples provided are indicative only.

Examples of relevant technical fields include (but are not limited to): predictive analytics; simulation; optimization; data visualization; network visualization; visual data analytics and optimization (image and video); data fusion and integration.

Areas of application are many and varied - examples include (but are not limited to): predicting buying patterns and trends, insurance claims, mortality rates, tax fraud, traffic patterns and delays, equipment failure, election outcomes, criminal/terrorist activities, and the spread of disease; improving healthcare outcomes; optimization of equipment performance and maintenance scheduling; optimization of manufacturing processes; predicting and optimizing traffic flow (internet traffic, road traffic, etc.); internet search; business informatics; logistics management; supply chain management; visualization of utility networks; climate modelling; enhancements to geographic information systems (GIS); crowdsourcing; detecting and preventing cyber-attacks.

IT11. Human-Computer Interaction; Virtual Reality; Augmented Reality

These three closely related fields encompass technologies that facilitate interactions among humans, computers and the external world and thereby enable many societally beneficial uses of information technology.

The field of Human-Computer Interaction (HCI) is focused on improving the efficiency and effectiveness of human-computer interfaces through the development of novel software and hardware designs to recognize and interpret human characteristics and behavior. Improvements in HCI technology can lead to enhanced virtual reality (VR) and augmented reality (AR) experiences by providing more natural and efficient ways for a user to interact with a real or virtual environment.

Technical sub-specialties within HCI are broad and varied, including (but not limited to): machine learning to anticipate and meet a user’s needs; speech recognition; voice control; gesture recognition (e.g., hand or eye tracking); behavior recognition; behavioral analytics; mood/emotion recognition; virtual assistants; visualization and display technology; tactile displays; haptics; biometric sensing; bioacoustic sensing; biosignal detection and processing. These technologies may be implemented on wearable devices such as smart watches, smart glasses and health trackers.

Virtual Reality involves providing sensory input to a user that replicates being present in a real or imagined environment. Most commonly the sensory input is limited to sight and sound, but it can also include other senses such as touch. Augmented Reality, on the other hand, involves a live direct or indirect experience of an environment, overlaid with computer-generated sensory input usually in the form of graphics, video and/or sound.

Applications of VR and AR include (but are not limited to): education - enhanced learning experiences; medical and healthcare - treatments for PTSD, phantom pain, anxieties and phobias, autism in children; support for complex tasks such as surgery, equipment assembly, or maintenance and repair by adding relevant information to the field of view of the user; training for medical personnel, law enforcement, military, and emergency responders; architectural design - experiencing a virtual building before it’s built; engineering and design; telepresence - for meetings and remote workers; market research - experiencing a virtual product that doesn’t yet exist; entertainment - cinema, music, and sports; tourism; product advertising and promotion; computer games.

IT12. Social Media; Collaborative Networking

This subtopic focuses on commercially viable information technology innovations that will add value to social, professional, business, or technical interactions over the internet.

Examples of relevant technical fields and applications include (but are not limited to): services based on crowdsourced information; collaborative healthcare; the sharing economy; professional networks; B2B networking; image and video centric networks; micro video; social networking tools; visual content optimization (image and video) for social media; video sharing.

IT13. Software

This subtopic focuses on information technology innovations that are embodied in software and provide important new or enhanced capabilities that will usually be generalized, rather than directed to a specific use case. Examples of such capabilities include (but are not limited to): enhanced computational speed or efficiency; new or improved functionality; improved or extended performance; increased ease of use and accessibility.

The range of possible innovations under this subtopic is too broad to attempt to describe here. Past examples of significant software innovations cover a wide range of technical approaches and resulting new capabilities, and include (but are obviously not limited to): Object-Oriented Programming; the GUI; HTTP; HTML; TCP/IP; SQL; internet search engine(s); the spreadsheet; word processing; MapReduce; virtualization.

IT14. Other

This general subtopic is intended to capture any information technology innovations that are not covered in the preceding subtopics and that have the potential to generate substantial commercial returns and lead to a positive societal impact.