The Infosys Labs research blog tracks trends in technology with a focus on applied research in Information and Communication Technology (ICT)

« May 2018 | Main | September 2018 »

June 29, 2018

Adaptive Inspection: Hurricane Season

 2017, hurricane Harvey and Irma hit the US coast with winds exceeding 130 miles per hour, leaving in its wake 103 people dead and an estimated damage of $200 billion.  The double whammy within 2 months of each other and the severity of the hurricanes is expected to slow US GDP by 1%.

In Florida alone, the total insured losses were estimated at more than $5.8 billion, with more than 689,000 residential property claims and 51,396 commercial property claims due to Hurricane Irma. Insurance companies were inundated with claims and scrambled to process the claims submitted by their customers. The frenzy was aggravated by the fact that Hurricane Harvey had hit Texas less than 3 weeks before Hurricane Irma hit Florida.

One of the greatest challenges that Insurers faced during the 2017 hurricane season was the shortage of adjusters. The first step for insurers to process claims was to have the adjusters visually assess the damage and estimate the loss. Unfortunately, most of the adjuster were in Texas assessing damage due to Hurricane Harvey leading to a shortage of adjusters in Florida and an increase in adjuster prices in the range of 15% to 25%. The shortage was only amplified by the lack of access and safety concerns.

Adaptive Inspection technologies which combine the capabilities of artificial intelligence in the form of computer vision and image analytics, and edge computing enable insurance companies to leverage autonomous agents such as drones to inspect property claims more efficiently and effectively. Drones are capable of flying closer to structures to capture miniscule details through high resolution images providing a more thorough report than humans adjusters while reducing the time from 1 hour to 15 minutes. Edge computing capabilities enable the drones to avoid obstacles, reach the location and provide images for the image analytics to analyse, estimate damage and create coverage reports.

his process lays redundant the erstwhile paper based process resulting in errors, and speeds up the claims process while preventing adjuster injuries. The technology can also be used to assess property damage in calamity affected areas before receiving claim requests in order to speed the process and prevent consumer grief.

Companies like USAA, AIG and Allstate have already deployed drones to enable adjusters to view hard to reach areas from a safe location and analyse the images. The technology has rapidly matured over the years and stands to change the way adjusters and insurance companies assess claims while changing the way organizations all over the world inspect their physical assets.


June 4, 2018

Blockchain Next: Social Media and AI

The Facebook data breach saga became a global phenomenon with reports suggesting that more than 87 million user profiles were compromised. The company lost over 14% of its market capitalization with #DeleteFacebook trending on Twitter. With over 3 billion active users on various social media platforms, this data breach might just be the tip of the iceberg.

Companies like Facebook and Google are built on a Surveillance Capitalism business model business model where they collect all available user information and harvest it so that they could effectively advertise to them. As per some estimates, Facebook controls 25% of the world's social media data and enterprises are leveraging this to create personalized advertisement strategies. This has fueled the social media marketing spend of enterprises which have almost tripled in the last few years.

The personalization models of these social media companies are reliant on the amount of information these companies capture as it is directly proportional to the performance of the AI engine. Google search results, advertisements on Facebook wall, movie recommendations by Netflix and voice assistants like Alexa are all driven by AI technologies and data is an integral part of these AI driven applications. AI applications are able to predict and recognize patterns by processing large quantum of historical data. The accuracy of these predictions are directly related to the amount of data it has been trained on and this leads to a data arms race among corporations. The flip side of these technological developments is the loss of privacy and data security.

This raises the question- Is there a better way to address data privacy issues without compromising on the benefits of AI driven applications?

AI driven applications built on distributed ledger technologies like blockchain could help users reap the benefits of these AI applications without losing control of their personal information. Today the data is owned by select few companies and they in turn sell that information. With distributed ledger technologies, users would be able to encrypt and track their personal information over a distributed network. Companies building AI applications would bid for the anonymized data on the distributed network and the user would get compensated accordingly depending on how valuable the information is for the company. The system would remove middlemen allaying data privacy fears as well as allowing users to earn profits in lieu of data.

Since metadata are not stored on centralized servers, third parties can't use user information for surveillance, tracking or data gathering. Startups like and are providing blockchain based solutions. While uses an ethereum blockchain network to validate various skills and qualities of users similar to LinkedIn, provides a blockchain based social dashboard through which users can distribute their information across various social media platforms.

Social media and AI applications built on blockchain could help create a network which has improved security and privacy offerings apart from allowing users to have better control over their content.