Unisys Hackathon 20/20

Diagnose sensor health and predict downtime
This is a known problem in IOT. There are thousands of sensors in numerous wireless sensor networks which are part of IOT installations. Many sensors are non-monitorable/accessible. Based on the recent data reporting by the sensors, the software should be able to predict downtime of that sensor. Also, one important point to consider is “where” you would want to place the software – possibly gateways? Another way of looking at it - develop an intelligent Gateway(software).

You are expected to use open resources for the relevant data or generate the dummy data if you have to.

Automatically validate identity without Identity card for organizations
We usually show our identity cards, swipe them at the gate, and then enter. An alternate way would be to have an intelligent device (or a set of devices – one with the individual and the other on the gate) or a software which can detect the identity accurately of the person passing through the gate.

Or, thinking aloud, could your mobile be used in a novel way?

We believe that because smart city programs are already funded and well formed, it makes them ideal contract vehicles for safe city initiatives. Smart city technologies can be adapted for public safety agencies. This will allow cities to leverage their investments for safe city programs faster and at less expense. Listed below are the desired outcomes and possible known gaps in making smart cities safer..

Desired Outcomes

• Enhanced synergy of existing Safe City solutions
• New marketable concepts to improve collective community security
• Ideas which help correlate Smart City programs to new Safe City projects

Known Gaps

• Connecting the Public Safety Continuum

  • Information systems still aren’t synergized

• Sovereignty Concerns

  • Borders from city limits to country crossings are porous

• Lack of Sensory Consumption

  • IoT information coordination is rudimentary

• Citizen Force Multiplication

  • The power of social media is underutilized

• Cyber Crime

  • Even if we knew the scope the problem seems insurmountable

• Good Lost its Advantage

  • Rebranding of police, fire officials as protectors is needed

• Things are Different

  • Infrastructure is aging, weather is worsening, the economy is lagging

It would be great if you can address any or all known gaps in your prototype.

Instead of SSL 256 any other algorithm/protocol that can be used for cyber security space. Do not consider obsolete industrial specifications.

As a submission we expect a webapp which should include this SSL Encryption Algorithm.

Scalable Machine Learning for Smarter Applications

Every company is now trying to be a data company, capable of using machine learning in the cloud to deploy intelligent apps at scale, thanks to the machine-learning trends. With hosted machine learning models, companies can now quickly analyze large, complex data, and deliver faster, more accurate insights without the high cost of deploying and maintaining machine-learning systems. Application intelligence is the process of using machine-learning technology to create apps that use historical and real-time data to make predictions and decisions to deliver rich, adaptive, personalized experiences for users. We believe that every successful new application built today will be an intelligent application.

Machine learning can be innovative if it proves to be a new way to gain previously impossible insights. It is not yet evident whether those insights are enough to make machine learning disruptive. Even though, the machine-learning field is maturing at this stage, but it still has unanswered questions about whether its efforts use artificially intelligent processes effectively to derive insights from data, and therefore produce actionable intelligence.

Using artificial intelligence to arrive at new insights is a more complex and challenging task than merely getting better quality results through the automation of data processing.

Come up with your own disruptive machine learning application with its relevant use case.

Predict the arrival of the next support issue for a product

Products which are already being used by a set of customers, tend to report defects from time to time. Often these defects occur in a few specific components of the products. Also, some customer setups report more defects than the rest. The idea is to analyze the history of defect reports and come up with a prediction on the next possible issue.

Come up with your own disruptive machine learning application with its relevant use case.

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 deals with the multiple subjects, their movement, synchronization of information, Geo-location, subject identification etc. can find numerous usage with the virtual simulation. Its usage into product development is immense, they not only help in discovering the hidden business cases which can be incorporated into the product but can also play an important role during product testing with better visualization.