The Spectrascapes Dataset

Akshit Gupta, Joris Timmermans,  Filip Biljecki, and Remko Uijlenhoet

A multi-spectral terrestrial-view dataset consisting of 17,718 street level multi-spectral images with Red, Green, Blue, Near-infrared, and Thermal spectral bands, captured using a custom hardware-software based platform which was deployed on bikes, across the Netherlands. Strict emphasis on data calibration and quality, and metadata fusion with Very High Resolution (VHR) satellite imagery at 30cm resolution.  Thus, enabling comprehensive street level and overhead view of built environment in urban areas.

UrbanScape Platform

A custom hardware-software based system for capturing multi-spectral imagery data with crowd-computing. Can be deployed on buses and trams (deterministic trajectory), or cars and bikes (random trajectory). Uses deep-learning on edge, to remove personally identifiable information and generate metrics.

Respire

This involves creating a low cost distributed sensor network for air pollution monitoring. More Details available here.

Won 2nd Prize in TU Delft Global Prototype Competition.
Nominated for
and
Won Encouragement Prize (Top 10 Innovative Ideas) at PHIA 2020 Idea stage, top 9 in Ideation Category of TU Delft Impact Challenge, was chosen as one of the 2 projects (out of 80) to represent TU Delft at the Dutch 4TU Impact Challenge 2020, Finalist of ClimateLaunchpad Netherlands 2021 and Winner (1st Prize) of ReadyToStartup by Yes!Delft and Rolland Berger in Feb 2021.

TreeScanner

A novel technique to opportunistically measure health of urban trees using sensors mounted on moving vehicles like taxis and garbage trucks. This was my masters thesis at TU Delft in collaboration with the MIT Senseable City Lab. Involves extensive use of custom developed deep learning-based models for fusing low resolution and high resolution sensor data on the edge device.

Tools and methods for monitoring the health of the urban greenery

Akshit Gupta, Simone Mora, Yakir Preisler, Fàbio Duarte, Venkatesha Prasad & Carlo Ratti

GreenScan: Towards large-scale terrestrial monitoring the health of urban trees using mobile sensing

Akshit Gupta, Simone Mora, Fan Zhang, Martine Rutten, Venkatesha Prasad & Carlo Ratti

To Trust or Not To Trust: How a Conversational Interface Affects
Trust in a Decision Support System

Akshit Gupta, Debadeep Basu,  Ramya Ghantasala, Sihang Qiu and Ujwal Gadiraju

This paper elicits research on trust development in decision support systems of the future using conversational and web-based interfaces using a crowd computing paradigm. Published WWW ’22.

Second Chance for a First Impression? Trust Development in Intelligent System Interaction

Suzanne Tolmeijer, Ujwal Gadiraju, Ramya Ghantasala, Akshit Gupta and Abraham Bernstein

This is a paper eliciting the elusive concept of trust in automated Systems. My contributions include the creation of scenarios for crowd computing tasks and overseeing the technical development. Published UMAP 2021 (29th Conference on User Modeling, Adaptation and Personalization)

mmWave (60Hz) based People Counting and Localisation

Prototyping and implementation of privacy preserving detection of social distancing and human localisation using millimetre Wave radar sensors (60GHz). This was a team project in response to Covid-19 with Erwin Russel and is continuation of our effort on a custom made android app based on WiFi and Bluetooth for contact tracing using indoor localisation. Under the guidance of Prof. Marco Zuniga and Prof. Fernando Kuipers.

AppButton (Formerly WhatsFace)- Android App

Simulates combining of Whatsapp and Facebook(Two apps that most people spend time in college). The app has currently more than 2,00,000 downloads on Google Play Store. A headache throughout as it suffered from trademark infringement from Facebook leading me to change the name and regular depreciating of Android APIs. A screenshot summary of installation data is available here.

Res-Queue

An AI based decision support system called Res-Queue was developed in 40 hours in HackZurich 2021. This helps rescue management control room to optimise rescue teams deployment during disasters by utilising a multitude of digital data.
This won the the Xylem Challenge at HackZurich 2021.

Penalty Shootout – Action on Google Assistant

Developed a game for Google Assistant that simulates penalty shootout using voice interface in the FIFA World Cup fever season.VUI using Dialogflow, Fulfillment in node.js. Published in Actions on Google Directory.
Has more than 5K invocations within first 20 days of launch.

This won the #IndiaBuildsActions campaign by Google India in 2018

When Google killed custom “Actions on Google” platform, this was depreciated.

Crypto Handler – Alexa Skill

Voice Skill for Amazon Alexa with multi turn dialog and understanding user context for getting the prices of various cryptocurrencies in various fiat currencies. Published in Alexa Skill Store.

LemonTea – Icon Pack for Android

Icon Pack for Android Custom launchers.Provides perfect icon masking for non themed icons. 300+ Icons Themed. Published in Google Play Store and has been downloaded more than 1000 times so far. A screenshot summary of installation data is available here.

Day Ahead Pricing forecasts in Power Markets based on RNNs

As part of course CS4240 at TU Delft, an independent reproduction of the results published in a paper based on BLSTMs  was performed on a different dataset from ground up. We describe the entire process along with our intuition as we moved through each step of reproduction as well as highlight the ambiguities present in the original text provided by the authors. Furthermore, we compare our results with those provided by the authors.

QuadRotor Drone

As part of course CS4140 at TU Delft, a quadroter drone was developed with custom firmware with custom roll, pitch, yaw and height control in a team of 4 students. A custom communication protocol was developed to control the drone from both the keyboard and the joystick. My contribution lie in the communication protocol design, yaw control implementation and custom P controller used in pitch and roll controllers.

Rider in the Storm- Control website using Voice

This is an action published on Google Assistant Directory which enables the controlling of this site using voice. Both the control device and the site can be on separate networks, thus simulating Machine to Machine Communication. When Google killed custom “Actions on Google” platform, this was depreciated.

Text Extractor for POI/POA

Android app which uses ML-Kit for on-device machine learning for text extraction from Proof of Address and Proof of identity. A pertained model from firebase is used. Open Sourced on GitHub.

Smart Home With Real Time Face Identification and Voice Control

Interactive and scalable Smart Home system with custom built hardware, firmware and open source Software and services.Machine Learning services used in backend server made the system cognitive.
Raspberry Pi used as Central Server and Hub running Home Assistant.
Azure Face API used for face identification and Alexa Voice Services used for Voice control.

Laplace Charge

For EIT Deephack Hacking Urban Mobility with IoT, we built a peer to peer platform for EV charger sharing.

It was awarded as the most implementable idea and first runner up in terms of cash prize, winning EUR 1500.

Intervalometer using 8085

An intervalometer was made using 8085 microprocessor which controlled DSLR and clicked photos at regular intervals as specified by the user depending on fps required .Later all these pictures are stitched using a pre made software to make a time lapse video.

Doctor Sugar

We built a conversational interface to be used diabetes patients along with a mobile based glucose detection module developed by Roche.

Our team was awarded 900 CHF and declared winner for the challenge proposed by Roche out of more than 1095 participants at HackZurich 2020.

Word Clock

A word clock based on Arduino. Micro controller level programming in objective C and ton of soldering leds. Made among the top five popular posts on reddit r/India for the day.

SeamEye

We have built a novel (no other research publication till date which utilises a similar approach) wearable device, SeamEye, to measure the bowling speed of cricket bowlers during training using low cost accelerometer, gyroscope and machine learning on the edge. A project which shows how physics, embedded sensors and machine learning can coalesce to solve a problem which was considered impossible till 2018.

Extensible Home Automation System in a Budget (HAB)

Made a home automation system using Raspberry pi as hub and Arduino as nodes.(Action node and Sensor node both).Here OpenHAB was used as central software controlling all the nodes which could be accessed from an app as well as web interface. Also, nodes could be added by the user on a plug and play basis.

RGB Mood Light

RGB light with over 16 million colors based on Arduino and can be controlled from an android app via bluetooth.