Participants are requested to choose their desired topic from the following list:
The combination of data streams and services created by digitizing everything creates four basic usage models — Manage, Monetize, Operate, and Extend. These four basic models can be applied to any of the four "Internets." Enterprises should not limit themselves to thinking that only the Internet of Things (assets and machines) has the potential to leverage these four models. For example, the pay-per-use model can be applied to assets (such as industrial equipment), services (such as pay-as-you-drive insurance), people (such as movers), places (such as parking spots), and systems (such as cloud services). Enterprises from all industries can leverage these four models.
Digitization and cheap storage has led to the generation of lots of data both structured and unstructured which we call Big Data. This along with advances in Machine Learning and Deep Learning has enabled us in two primary ways. One is to be able to understand the complex interrelationship of data thus helping in deriving hidden patterns in data enabling us to make better business decisions like do predictive and prescriptive analytics. The second is to automate processes and bring in intelligence into digital things. With faster data management and computing technologies available, it has also become imperative to come up with intelligence based on data and information that is real time or near real time. Use of Analytics, to come up with Cognitive (Human Like) and Intelligent interactions in a B2C scenario, is becoming more prevalent. This helps in better personalization and reduces operations costs for businesses. Other than customer generated data which includes open data sources and the dark internet, today sensors, chips, machines, and other digital devices generate time series/stamped data which also interact with each other for various outcomes. IoT Analytics deals with this stream of Analytics primarily.
We are interested in developing solutions in each of the areas talked about above. Predictive Maintenance Solutions for IoT equipped devices, cognitive interfaces like Chatbots and contextual text miners using NLP, Deep Learning-based Picture and Video recognition solutions which can go beyond face recognition but can identify from other pictures like X-Ray scans and others, Bayesian Network-based Anomaly Detection and outcome predictors, and Neural Network driven decision and automation management systems are examples of some of the solutions and capabilities being looked at and developed at Unisys. We use the latest codebases and platforms to build our solutions on Amazon clouds and other APIs and codebases provided by Python, Google APIs etc.
The convergence of cloud and mobile computing will continue to promote the growth of centrally coordinated applications that can be delivered to any device. Cloud is the new style of elastically scalable, self-service computing, and both internal and external applications will be built on this new style. In the near term, the focus for cloud/client will be on synchronizing content and applications across multiple devices and addressing application portability across devices. Over time, applications will evolve to support simultaneous use of multiple devices. In the future, games and enterprise applications alike will use multiple screens and exploit wearables and other devices to deliver an enhanced experience. Example: As the need for cloud based apps and services continues to grow, there will be a need for a development model for these applications and services, which will support the cloud based software development lifecycle.
Microservices
For simple and limited scale applications, monolithic architecture is still relevant. For modern cloud applications that require agility scale and reliability, Microservices Architecture offers great promise. A Microservices application is composed of independent components called ‘Microservices’ that work in concert to deliver overall functionality of the application. Unlike Monolithic applications, Microservices applications enable the separation of application from underlying IT infrastructure.
With mobile phones becoming more powerful, there is increased emphasis on serving the needs as well as harnessing the power of the mobile user in diverse environments, as opposed to focusing on devices alone. For example, backend processing for data personalization and patternization, and use of these patterns to create more effective and efficient context sensitive information sharing for the end user’s benefit.
Ubiquitous embedded intelligence combined with pervasive analytics will drive the development of systems that are alert to their surroundings and able to respond appropriately. Context-aware security is an early application of this new capability, but others will emerge. By understanding the context of a user request, applications can not only adjust their security response, but also adjust how information is delivered to the user, greatly simplifying an increasingly complex, computing world.
One of the top concerns expressed by IT managers in recent surveys regarding their reluctance to move business critical applications into a cloud environment was security. Most of the security concerns stemmed from external attacks such as malware, denial of service, and hacking. We are looking at submissions that attempt to solve these issues. Are there new threats on the horizon that might specifically target a cloud provider? How would you prevent them? You can also consider various scenarios like secure data for multitenancy, computation of encrypted data etc.
Computer Scientists around the world are doing extensive research in different areas. Few of these technologies may emerge and change computing in the near future such as Block Chain Cognitive Computing, Application Defined Data Center, Micro segmentation, and Fintech (Financial Technology). We are looking at submissions that come up with innovative ideas in these areas, addressing various aspects of implementation and usage.
Be it large, small or medium sized, every business is now talking about cloud computing. Airports are no different. Fundamentally, airports are like clouds that provide a shared network, shared check-in systems, baggage reservation systems, and other IT infrastructure that is leveraged by all airlines operating in and out of the airport. Airport operators are under constant pressure to maintain a state-of-the-art IT environment, but find themselves year-on-year with shrinking IT budgets. We are interested in papers that explore the various solutions in an airport that can be part of a cloud and intelligibly analyze the tangible and intangible benefits that would accrue by implementing such solutions.
Virtual Simulation
Virtual reality simulation is the use of 3D objects and environments to create immersive and engaging experiences. Transport products such as Airline passenger service, Airline cargo, Airport operations etc. which deal with the multiple subjects, their movement, synchronization of information, geo-location, subject identification etc. can find numerous usage with Virtual Simulation. Its usage in product development is immense. They not only help in discovering the hidden business cases which can be incorporated into the product, but also can play an important role during product testing with better visualization.
Software Telemetry Service
Telemetry includes capturing, processing, and interactive display of software usage trends. Data regarding an application’s usage along with users’ profile (keeping PII -Personally identifiable information - outside) is gathered from multiple channels. All ingestion points contribute data towards a single repository. Analytics are developed against this data repository to understand usage trends based on different personas which allow product team to understand the impact areas for further focus and derive business insights.
DevOps is the latest software industry practice that aims at establishing a culture and environment for building, testing, and releasing software rapidly, frequently, and more reliably. DevOps is considered as an emerging practice which is an intersection of traditional Development (Software Engineering), Software/IT Operations, and Software Quality Assurance (QA). Software industry is rapidly embracing DevOps to achieve improved productivity/Improved customer experience/Improved quality and reduced risk of software delivery. DevOps uses multiple tools required to code/build/test/package/release/configure/monitor software products and applications. Open Source tools such as Docker (containerization), Jenkins (continuous Integration), Puppet (Infrastructure as Code) and Vagrant (virtualization platform) among many others are often used by DevOps practitioners. Contestants can design, develop, and demonstrate a working POC of DevOps using available tools or build new tools to achieve DevOps practice. The demonstration should reflect benefits of DevOps on any one of the aspects such as code/build/test/package/release/configure/monitor software products and applications.
Multi-model Biometrics are fast becoming the go-to security option for enterprises that want to offer the most secure authentication and the most convenience for their customers. Multi-modal authentication benefits the enterprise in three specific ways. It vastly improves the customer experience with no cumbersome passwords to remember. It improves the security of traditional authentication and prevents hacking and data breaches. We are looking for new ideas around it and use cases, it could be anything from biometric verification, image verification or design ideas which can be used across multiple industry/ business domains ranging from Financial, Transportation & Logistics, Social services, Safe cities, and Life sciences & Health care.
