Artificial intelligence in Airport?

Anyone and everyone who has travelled by Air knows the importance of time.   Airlines advice passengers to reach airport at least 3 hours before flight departure and for international flights and about 2 hours for domestic.  While passengers enjoy being in the retail area of airport but unfortunately most of this time is spent standing in queues for checking and security clearance. 

Globally, the average time spent at an airport — from arrival until an aircraft’s doors are closed — was 133 minutes in 2014. Out of this time only around 30 minutes is spent by the passenger having relaxing time in retail area. The time consuming process in airports include- Check-in/bag drop, Security, Orientation, and Boarding. This is a loose- loose situation for everyone. Passenger’s experience is bad as he has to wait in the queue. The airlines cost is more because they have to put extra staff to handle customers, the Airport security time staff also need to spend more time.

The best possible outcome for an Airport is when passenger spend more time in retail area, which would result in more sales in these area which in-turn in more revenue for airport.  Airports around the world have transformed into a high tech, heavily secured shopping malls to capitalize this opportunity.  Which the concept of duty free purchase, it give added incentive to passengers to purchase.

Many processes have been introduced that have reduced the queue time for passengers. Airlines provide option to passengers to web check-in and use home printed bag tags. When they reach airports they just need to drop their bag and proceed towards security.  In US the TSA, who is responsible for airline and airport security has introduced a pre-screening program called TSA Precheck. Through this frequent flyers can enroll to the TSA precheck program, on enrolling they would be issued a Known Traveler Number (KTN) after successful background check. When they reach airport they have a special queue for security clearance which is many times faster than regular queue. All these initiatives have helped reduce the time spent by passenger in queues, but with limited success. The problem is the TSA Precheck is not available to everyone e.g. non US resident, and not everyone wanted to go through the process of getting the KTN number.

Now coming to the main problem, how can airports process be streamlined to ensure all passengers spend more time in retail area then in queues? This is where technology and in particular AI and biometrics can play a major role. Many recent developments in AI technology has introduced algorithms that can detect human emotions, this enables the system to see if a person is stressed or scared. This technology is maturing fast and many leading players including Microsoft has adopted it. This would enable profiling of people with bad intentions. This could be clubbed with facial recognition and government database check to ensure the profiling is done properly. This would mean that only suspicious passengers go through extra checks and frisking and all others can basically clear security check in seconds.  This can go a long way in making passengers less hassled in airports. This saves time and cost for airlines also as they don’t have to send passenger information to government agencies for domestic flights as required by many governments. When passenger spends more time in retail area rather than in queues, it’s a win-win for everyone.

Although this technology is in early stages and would need manual interventions in the initial phase, with machine learning system would get smarted day by day and at some point would be able to handled security checks on its own in a fully automated way. The future is promising.

My Objective of the year – Reduce the waste of the ideas!

Waste always bothers me.  I am sure it does to many of you as well.   What are the common wastages you can think of?  Close your eyes and think of wastes that really bother you and what you can do about it?

 

 

The above will be common thoughts that more than 80% of us will come up with!    I am sure some of you thought of Money when thinking of waste as well.  Did you come up with some other “thought” when thinking about waste?  Do let me know in the comments below what are the other wastes that bother you and more importantly what are you doing to address the waste or prevent it? 

My area of concern about Waste might surprise many of you.  Have you ever thought of wasted idea?  What is wasted idea anyway?  Wasted idea is an idea which did not really see light of the day just because it was not articulated properly, it did not get a supporter or sponsor for it, maybe it was just way before its time or some other reason.   For many of you who have been in computer industry for long time, you have seen that AI was talked about even 20 years back, lots of research work and concrete algorithms were developed many many years ago and if that was the case – why we did not doing smart things that we do with AI few years back?  IMHO there was a crucial piece of the puzzle that was blocker was the compute power and storage.  Don’t you believe me? Read the following article https://en.wikipedia.org/wiki/History_of_artificial_intelligence

 

Now with the easy availability of compute and storage power , AI is seeing new usecases and today its used in many many extra ordinary ways but imagine if that had not happen?  AI would have been such a big wasted effort!  A good idea which has potential did not make it just because it was before its time.  Simple isn’t it?  So what can we do about it ?  Or should we do anything about it at all?  I am for sure on a journey to eliminate as much waste as possible from the various innovation activities that we do within the organization.  Do you do innovation activities in your organization?  What do you do with the things that you generate/create after activity is done?    My common observation from being part of such activities in my organization as well as interviewing several people who are associated with innovation is , we have not quiet cracked the problem of how to identify the idea which is a total “junk” idea v/s the idea that might need some more thought before we can make decision on it.   It’s the latter category of idea that I call the wasted idea as more often than not, after the innovation activity is done, these ideas are shelved and no one looks at them again.  Should we be doing things differently?  How do we give second chance to these ideas?  Look at potential of merging of one or more ideas and creating a new idea altogether?    If this idea is real for you and you are interested in solving the problem with me! Please do reach out to me and we will find out ways and means to help each other out!

 

 

Image source:

1.       http://www.independent.co.uk/news/business/news/the-obscure-reason-why-supermarkets-are-allowed-to-send-food-waste-to-landfill-a6861196.html

2.       https://www.shutterstock.com/video/clip-11650187-stock-footage-thematic-hd-stock-footage-on-save-water-theme-water-leaking-from-pipe-wastage-stock-movie-clip-on.html

 

 

Can Unisys ride the Artificial Intelligence wave?

Artificial Intelligence is not a new term to the industry, having been coined in 1955 by John McCarthy. However, the usage of AI has been dormant over the years, primarily because of limitations imposed by hardware and data. After six decades of chequered history, AI is making a comeback because of the advancements in hardware and the way how we store and manipulate huge amounts of data structured and unstructured data. Unisys has products like Elevate, Digistics and LineSight that span a wide array of industries like Finance, Transportation & Cargo and Safe Cities. Let us take the financial sector for example, a sector which AI is taking by storm. Can Unisys ride the Artificial Intelligence wave?

Almost every financial company is started using AI to reduce costs, enhance the customer experience and optimize their processes. For example, JPMorgan Chase’s Contract Intelligence (COiN) platform uses image recognition software to analyze legal documents and extract important data points and clauses in seconds, compared to the 360,000 hours it takes to manually review 12,000 annual commercial credit agreements. According to a 2015 study by research firm Javelin Strategy, false declines, legitimate transactions that are wrongly rejected, account for $118 bln in losses for retailers. A third of false decline cases result in lost customers, and in US alone they incur damage that is worth 13 times the value of actual fraud. The widespread adoption of AI across industries is predicted to drive global revenues of $12.5 billion in 2017 and $47 billion in 2020 with a CAGR of 55.1% from 2016 to 2020. Given the direction that the market is headed towards, there is clearly a lot of potential in these domains.

Some might say that it is too late for a new player to enter the AI industry. However, AI is not all technology. It is both a technology and an art. Today, getting the data is not the challenge. Everyone has a different perception of data and how to get insights from it and for this very reason, I believe that it is never too late for a new player to enter the industry. If someone has a better algorithm, they can compete with the best in the market because their solution will be provide an improvement in profits and reduction in costs which is actually the main goal. Then comes the idea of security. Unisys has security in its DNA. Our customers trust us with their data on our servers. We can leverage this trust and provide better products and services to serve our customers.

Artificial Intelligence is still evolving and has a long way to go. Unisys still has a great chance to get into this market and disrupt it.

Sources: 

1. https://www.toptal.com/finance/market-research-analysts/artificial-intelligence-in-finance

2. http://www.cmo.com/features/articles/2017/8/24/15-mindblowing-stats-about-artificial-intelligence-dmexco.html#gs.kQfReEY

Everyone is an innovator !

Innovation as a word can create confusions in many people's minds and have a feeling that it is for intellectuals. That is a myth that needs to be busted. Everyone is an innovator. In fact innovation keeps happening without one knowing that they are an innovator.

 The fundamental thing one needs to understand is that Innovation happens when you look at solving a challenge faced. Example of a challenge can be in our day to day work that we go about. How can I improve my quality of deliverable? First thing to do is what am I doing as part of my work and what help do I seek to get the quality verified. Do I get called by my peers for review of quality? Is this something that can be referenced as a good practice that can be adopted by everyone in the team which will lead to consistent quality across all the team members? Can we bring predictability based on repeated approach?

 If the answer is Yes, then you have achieved Innovation in your area of work. We can always start with addressing challenges however small they are in nature and get towards a better tomorrow.

Innovation will kindle the energy dormant in every individual and having your curiosity quotient high and help keep your work place and surroundings enjoyable.

As I close my blog I would like to throw up one use case of automating Unit testing. We have recommendations of tools like NUnit, JUnit for unit testing which will help the developers ensure better coverage of their user stories and at the same time bring up the efficiency of their work. We can definitely look at improvement of at least 5 - 10% improvement in productivity.

 

I did refer to the blog on the importance of innovation

http://www.paggu.com/getting-into-roots/what-is-innovation-why-innovation-is-important/

 

 

Can you identify the plane that just flew by?

Apple's Siri has surprised everyone with its abilities to understand human voice and take action on various commands. It has brought human interaction to the digital world closer than ever before. But what if I tell you that my application Stri (Sixth Sense Search, pronounced as s-T-ree) can understand and answer humans like humans?

Lets try an example in google.com. Search for "Can you identify the plane that just flew by?". Here is the result.

Ooops. No result. Google couldnt tell you that it didnt know the answer. What it could do is to search for pages that has the maximum hits to the keywords you wrote! Are you satisfied?

Lets see how Stri handles the same request. Here is the result. 

So what are we doing here?

We, in Stri, have revolutionized the way digital data is interpreted, stored and retrieved. When a user searches for content, Stri analyses the content and looks for real life data that matches the query. The most difficult aspect is to understand the different objects in the query, use different real-time parameters such as location and time to build the appropriate question. For this specific example, we have identified the search query as "Can you identify the plane that flew by at 12.30PM in Sanjaynagar Bangalore?". The next is to identify on what is the search query related. Here the object is "Plane". So we have 3 critical information with us: Plane, 12.30PM and Sanjaynagar. Finally, the action is to be done is "Identify". Multiple keywords would still mean the same, such as, list, find, identify, search etc. Finally, we have identified the task: "Search for planes that flew over Sanjaynagar at 12.30PM"!!

Stri's approach to solve the problem is to use open databases. Stri has provided a wrapper to many services such as flight, train, public transport, media, tv etc. With the wrappers, Stri can connect and fetch details for various query string, retrieve results and post it back to the Stri search engine. Stri engine then collects information, with confidence numbers and posts the results.

The technology can now be extended to a number of dimensions! One can actually search when he visited Paris based on flight details / email details or check-in information in facebook. Or it can extend to devices that the user owns or his friends. This is definitely a wave that will carry everyone with it on the internet!

Managing the most important project of our life called "LIFE" !

Introduction:
These days it is so common to have most of our everyday tasks and searches done online through hundreds of websites and services.
So many of our everyday tasks starting from searching for house/property ,looking for good travel deals , searching for reviews on school for kids , looking for reviews of household items or buying them online , looking for job also including searching for matrimonial alliances or business partners happens over the internet. Come to think of it , we are spending so much time online ..
Haven't we all  spent hours together on the internet - searching and then saving the data relevant to us either copy pasting info or saving them as bookmarks or taking printouts.

What if your whole online experience during different stages of our life can be integrated & managed by something like a "Life Project Manager" .

We have so many tools help manage our profession life .. why don't we give the same importance to the most important project of our life called "LIFE" !

Some Concepts:
Currently our web browsers do not really keep a context of what we are looking for at all times , even if they do, they do it to collect information to suggest good ads or for their business needs or analysis.

A "life project manager" would ideally have at least the following concepts :

Create a life project:
We could have a desktop/hosted tool , that is built on a user centric manner , that allows the user to
create specific personal projects . The project could deal with anything like a job search that he is pursuing or
a online property related search , or  maybe just collecting review on a particular interest .

Collect ,customize and store meaningful data:
Allows him to collects as much data from various online resources from within the tool . The data collected can
be stored in this tool ,along with the user comments or his own research and analysis in one single place.
For Eg : During a house  search process , the user might have collected more info or updated data on a current property by actually visiting the site , he will combine the online and his current research data and store it in the tool in a project which he could call "My House Search"  .

Sharing /Collecting Review  :
The user can chose to share specific projects like "My House Search"  with his family/friends to either help him review his options or just to help them with their own property search.


Create Multiple projects:At any point of time , there will be so many things happening in your life .
You could be searching for a new property and at the same time you would be looking for a new school for your kid
or thinking of changing you job .
You could creating multiple projects of your life in this tool and track them and work on them as and when you have time.Since this will contain the records of all your past work and research on that area and you can discontinue and resume at any point.

Further enhancements :

1. We could have a online sharing mechanism to look at the important experiences of people in our circle and re-use  some of their resources or at least learn from their experience.

         For Eg. : we would definitely like to know the experiences of school search or reviews of    
         different schools  from the parents and we would definitely learn from their project "school"
    
     2.We would enter our personal details like location or addresses , personal preferences, stage of 
          life etc  in this tool , that can help in customizing our search experience on the net.


Some more Use Cases : 

Authors /Writers :
Assuming that the author/writer is working on many books/articles simultaneously
he would have collected lot of material /emails /suggestions from different people
and also from the internet for each of this. The tool can allow him to create
different projects for each of his works and then then track each of them
along with the data collected for that item.

Setting up a house :
This is really choatic project if not managed well. There will be so many things to buy online
to read reviews and collect opinion , get the best deals online and track several items like
interior design , plumbing ,electrical works etc.
All the online activity on each of these items and its result can be individually stored and tracked
with this tool.


Conclusion :
On the whole we know the internet is a huge ocean of data and resources that are waiting to be explored . But many a times this often leads to very unorganized or chaotic browsing patterns and very less meaningful data collected or atleast stored for future reference or sharing.

The tool will hopefully try to reduce the chaos in our "online" life and better manage the most important projects of our life.

Long live the internet!

Big data & Intuit? Nahhhhh.. it will never work!

Big data & Intuit? Nahhhhh.. it will never work!

Intuit is extremely good at adapting to technology & changing priority based on the trend. However, for some genuine reasons (that I am not aware of) Intuit is lagging way behind in making use of Big data to enhance the customer experience, improve product offerings & generate more revenue.

What are the key challenges that I could think?

- Legal aspect of the data needs to be taken care of

- Adding ability for traditional products to send data/analyze data is a challenge

- Handling multiple streams of devices/technologies to talk to a single platform

- Willingness of the customers/user to share data is a big challenge

Options currently available to address the challenges

- Technical limitations to handle big data are not an open question anymore. With Intuit deciding to use Amazon Web services (Amazon cloud) to host web sites & manage web applications, we are all set to receive big data from customers

- With the introduction of smart phones, multiple streams of device can easily talk to each other today. We can sue simple proven technologies like SOAP or REST based web services to make sure Intuit data services are platform/device independent

Next steps...

There two big challenges that would require a mindset change & would require involving discussions. Legal aspect of the data to be collected can be handled by making sure we meet all regulatory laws/policies. Once this is taken care of, we have a clear segregation about what data can be collected & what cannot be.

Based on the above analysis, we can always enable the feature on a limited set of products to collect legally allowed data on cloud. Analyze the data collected & make recommendations that will enhance the user experience. We can always run a pilot product with limited number of customers to understand the way users are reacting to this. Users can be provided with an option to opt out from sending any data.

Examples on where we can make use of the data

Specific example 1: Vendor scenario or supplier scenario

A small business employer decides to set up a new door manufacturing business.

He buys quick books and sets up a new company file. When setting up a company file, the recommendation engine based on the location and the type of business selected sends recommendations about possible suppliers and vendors which will aid him to set a company with ease and trust.

For Example; door delivery business, door knob supplier, hinge supplier and/or supplier details can be recommended for this user.

Specific example 2: Bank example

In collaboration with financial institutions, Intuit can recommend other financial institutions  for the employer to save money.

For Example,  let us assume that the property insurance at bank ABC is being paid $1000 every year. If bank XYZ is providing the same insurance at $900 a year, by this recommendation, a user can use $100 each year. 

The same recommendation can be applicable for other expenses.