- 👋 Hi, I’m Himanshu.
- 👀 I’m interested in SDN and IoT.
- 🌱 I’m currently learning networking, high-level and low-level design.
- 💞️ I’m looking to collaborate on SDN, Embedded Systems, DLMS/COSEM smart meters.
- 📫 Reach me via:
CGPA - 8.143/10
Projects:
- DLMS/COSEM implementation on following platforms:
- Linux (Ubuntu, RaspberryPi)
- STM32F207ZG
- MERN website for displaying smart meters data.
- DLMS-Wireshark for displaying expanded (array and structure in) DLMS normal packets in Wireshark.
- SDN TCP SYN flood detection and mitigation (ongoing).
CGPA - 8.383/10
Projects:
- FPGA-based implementation of Numerical Overcurrent relay.
- Industry-Oriented Project: Apportionate Battery-Capacitor (ABC) for Electric Vehicles.
- B.Tech. Project: 3D real-time mapping using Kinect v2 vision sensor in ROS environment.
- Percentage - 93.8%
- CGPA - 9.6/10
Projects:
- Cross-lingual text classification
Projects:
- Vehicle Control Unit (VCU) for Formula Student race car for Formula Green 2020 competition.
- DLMS/COSEM implementation on Linux (Ubuntu, RaspberryPi)
- Implemented Register class in fork from EPRI:DLMS/COSEM in collaboration with github:sudeshna
- Implemented a Data Compression algorithm in Python and integrated with the inter-host DLMS/COSEM communication using TCP/IP and shared memory approaches for inter-process communication.
- Implemented the Data Compression algorithm in C/C++ using TNT Matrix libraries. This allowed implementation of the complete application in C/C++ completely, and a seamless transition of the algorithm to STM32 implementation later on.
- Deployed 10 RaspberryPi-based DLMS/COSEM-enabled smart meters around IIT Delhi campus.
- Deployed a DLMS/COSEM-enabled Head-End System on Linux VMs hosted on IIT Delhi Cloud - Baadal - for collecting data from the meters at r intervals and store in MongoDB database.
- DLMS/COSEM implementation on STM32F207ZG
- Modified Linux libmodbus library to integrate to STM32 application, exposing read, write and delay functions for custom handling of modbus requests/responses.
- Implemented ESP8266 libraries in two different ways to integrate with multi-threaded STM32 DLMS/COSEM application in collaboration with github:venus696.
- MERN website for displaying smart meters data
- Hosted on Linux VMs on IIT Delhi Cloud - Baadal - accessible over IITD intranet for displaying data collected from the deployed smart meters.
- The website is written for two projects - Air Pollution Monitoring Device (APMD) and Smart Meters (SM).
- The website allows selecting a date-range or a rolling-plot option, and desired metrics from a list of available metrics.
- OpenLayers used to render a map of IIT Delhi with an additional layer with overlays to show checkboxes with location-popups marking locations of the installed smart meters around the campus.
- DLMS-Wireshark for displaying expanded (array and structure in) DLMS normal packets in Wireshark
- Modified fork from matousp:dlms-analysis github repository in lua to expand and display the COSEM structure and array (ASN.1 format) DLMS normal packets in Wireshark.
- Developed Vehicle Control Unit (VCU) for Formula Student Electric race car as per Formula Green 2020 rule-book:
- Shutdown circuit to control and cut power supply from battery to motor controller (and motor).
- Several PCBs (schematic and layout design, and soldering) to control the shutdown circuit.
- Programming STM32F103RB controller for algorithms to implement some controls in and out of rule-book.
- SPI communication of the STM32 board with an ADC and an nRF24L01+ board.
- Sentiment classification for a target language for which only small amounts of labelled data is available using transfer learning on a source language for which large datasets for the same are available:
- Sentiment classification training of base layers of the Adversarial Network model on source language datasets.
- Adversarial training with language detector branch of the Adversarial Network model.
- The model was implemented on Tensorflow-Keras framework for Amazon reviews dataset with English as source language and French as target language.