Author: kousik

RFID Scout Dashboard

RFID Scout Dashboard is used along with the RFID Scout IOS application for the following

RFID Audit Analysis: Provides complete analysis of the RFID Audit performed using the RFID Scout application. It provides a detailed error analysis report.

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Inventory Count Reporting: Displays the detailed report of the inventories available. Users can configure a minimum threshold for inventories and all the products below the threshold count are displayed in the dashboard.

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RFID Scout

RFID Scout works with a Zebra RFD8500 RFID reader. It can be used for the following tasks.

RFID Auditing: RFID auditing is simplified by the use of the mobile app. The application reads the RFID tag and the barcode and validates both the information. The dashboard provides a detailed audit report with the discrepancies observed during the audit.


RFID Tag Identifier: Assist in the identification of RFID tag model by narrowing down the list of potential tags based on the information from the RFID tag.


RFID Inventory: RFID Scout can be used to perform RFID inventory (or cycle counts) checks. The RFID inventory data can be exported as a CSV file or can be accessed from an online dashboard.

Sequoia Hackathon 2015


Showcased a wearable solution that improves the quality of life of elderly patients suffering from incurable diseases like Alzheimer’s, Dementia or Parkinson’s. By tracking patient’s daily activity patterns and by using a combination of supervised and unsupervised machine learning models to classify anomalies, we showcased abnormal behaviours and danger can be detected to alert the caretakers.

LogBase Security – How do we keep things secure?

LogBase Corporate Security

Compromising an employee laptop/account is the most popular method to gain access to a corporate environment. So we take extra care in protecting our corporate IT systems.

  • All employee laptops are encrypted.
  • Email and other accounts are protected using multi-factor authentication.
  • Employees use secure VPN connections to connect to the backend infrastructure.

Save The Hacker 2015

Save the Hacker

Built a reality game to score drivers based on their driving behavior. Users can challenge friends or random people on specific routes to see who is a safer driver. We used mobile phone sensors to gather car dynamics data and applied machine learning to classify the drivers based on how safe they drive.

Kovai Techathon 2015


Prototyped an app that predicts the road conditions and alerts users about potholes and speed bumps as they travel. We crowdsourced data from mobile sensors as people travel and use machine learning to accurately classify and predict the potholes and speed bumps.