website design | UCSC OSPO

Environmental NeTworked Sensor (ENTS)

Fri, 30 Jan 2026 00:00:00 +0000

ENTS I: Usability improvements for visualization dashboard

Topics: Data Visualization, Backend, Frontend, UI/UX, Analytics
Skills:
- Required: React, Javascript, Python, SQL, Git
- Nice to have: Flask, Docker, CI/CD, AWS, Authentication
Difficulty: Medium
Size: Large (350 hours)
Mentors: Colleen Josephson, Alec Levy, John Madden

The Environmental NeTworked Sensor (ENTS) platform, formally Open Sensing Platform (OSP), implements data visualization website for monitoring microbial fuel cell sensors (see GitHub). The mission is to scale up the current platform to support other researchers or citizen scientists in integrating their novel sensing hardware or microbial fuel cell sensors for monitoring and data analysis. Examples of the types of sensors currently deployed are sensors measuring soil moisture, temperature, current, and voltage in outdoor settings. The focus of the software half of the project involves building upon our existing visualization web platform, and adding additional features to support the mission. A live version of the website is available here.

Below is a list of project ideas that would be beneficial to the ENTS project. You are not limited to the following projects, and encourage new ideas that enhance the platform:

Drag and drop charts functionality
Creation of unique charts by users (with unique equations)
Customizable options of charts (color, line width, datapoint/line style, axis labels)
Exportable charts (with customizable options)
Saving layouts via url

ENTS II: Migration to TockOS

Topics: Embedded system, operating system
Skills:
- Required: Rust, C/C++, Git, Github
- Nice to have: STM32 HAL, python
Difficulty: Hard
Size: Large (350 hours)
Mentors: Colleen Josephson, John Madden

The current version of the hardware firmware is implemented in baremetal through the use of STM hardware abstraction layer (HAL) drivers. We are interested in porting the firmware implementation to an operating system (OS) to allow for additional functionality to support environmental data logging. TockOS is an embedded operating system designed for running multiple concurrent, mutually distrustful applications on low-memory and low-power microcontrollers that will be used. TockOS allows for OTA updates, dynamic app loading, hardware multiplexing, and more. We envision multiple users utilizing shared ENTS hardware that provides communication and measurement capabilities. Thus, the initial cost of deploying wireless sensor networks is reduced.

The TockOS kernel is written in Rust to enhance security. Userspace apps can be written in either C, C++, or Rust. Development will be done through a remote development server to access the hardware. See the following repos for the current status of the project:

Userspace library: libtock-c
Kernel: tock
Baremetal: ENTS-node-firmware

Scope of work:

Writing kernel peripheral drivers.
- Done entirely in Rust.
- Low-level understanding of microcontroller
- Basic kernel functionality knowledge.
Porting baremetal components to userland apps.
- Involves porting STM HAL calls to TockOS syscalls.
- Primarily done in C.
- Understanding of syscalls.

Develop a clean and intuitive web-based interface for WildberryEye

Sun, 15 Jun 2025 00:00:00 +0000

As part of the WildberryEye, my proposal under the mentorship of Isaac Espinosa aims to develop a clean, intuitive, and responsive web-based interface to support real-time pollinator detection, data visualization, and system configuration.

WildberryEye leverages edge computing (Raspberry Pi 5) and object detection (YOLO) to monitor pollinators like bees and hummingbirds. The expectations for this project focuse on developing a full-stack web interface to support real-time pollinator detection, data visualization, and system configuration. The whole development also include the real-time data extraction from the Raspberry Pi 5). The final result empowers researchers and contributors to engage with environmental data in an accessible and meaningful way.

WildBerryEye

Tue, 11 Feb 2025 10:15:56 -0700

WildBerryEye leverages Raspberry Pi and YOLO object detection models to monitor pollinizers like bees and hummingbirds visiting flowers. This initiative aims to enhance environmental research by automating data collection and analysis of pollinator activities, which are crucial for ecological assessments and conservation efforts. The project utilizes video data provided by Dr. Rossana Maguiña, processed through advanced machine learning techniques to accurately identify and track pollinator interactions in natural habitats.

Develop web-based user interface

Topics: Full Stack Development React Flask
Skills: Experience with full stack development and real time processing
Difficulty: Moderate to Challenging
Size: Medium or large (175 or 350 hrs)
Mentors: Carlos Isaac Espinosa Ramirez

Develop a clean and intuitive web-based interface for WildBerryEye, ensuring ease of use for researchers and contributors. The platform should present real-time pollinator detection results, facilitate data visualization, and allow users to interact with system settings efficiently. The website must be accessible, visually appealing, and optimized for both desktop and mobile users, avoiding unnecessary complexity or intrusive elements.

Specific tasks:

Frontend Development: Continue development to enhance the user interface using React and CSS, ensuring a responsive and user-friendly design.
Backend Development: Expand functionality using Flask, focusing on efficient API endpoints and seamless interaction with the frontend (excluding database implementation).
Real-Time Communication: Implement and refine real-time updates between the frontend and backend to enhance system responsiveness.
Usability & Design Optimization: Research and propose improvements to the system’s usability, design, and overall user experience.

Environmental NeTworked Sensor (ENTS)

Fri, 31 Jan 2025 00:00:00 +0000

ENTS I: Web portal for large-scale sensor networks

Topics: Data Visualization, Backend, Frontend, UI/UX, Analytics
Skills:
- Required: React, Javascript, Python, SQL, Git
- Nice to have: Flask, Docker, CI/CD, AWS, Authentication
Difficulty: Medium
Size: Large (350 hours)
Mentors: Colleen Josephson, John Madden, Alec Levy

Below is a list of project ideas that would be beneficial to the ENTS project. You are not limited to the following projects, and encourage new ideas that enhance the platform:

Improve streaming functionality
Generic interface for sensor measurements
Logger registration
Over the air (OTA) configuration updates
Implement unit tests and API documentation

ENTS II: Hardware to for large-scale field sensor networks

Topics: Embedded system, wireless communication, low-power remote sensing
Skills:
- Required: C/C++, Git, Github, PlatformIO
- Nice to have: STM32 HAL, ESP32 Arduino, protobuf, python, knowledge of standard communication protocols (I2C, SPI, and UART)
Difficulty: Hard
Size: Large (350 hours)
Mentors: Colleen Josephson, John Madden, Jack Lin

The Environmental NeTworked Sensor (ENTS) node aims to be a general purpose hardware platform for outdoor sensing (e.g. agriculture, ecological monitoring, etc.). The typical use case involves a sensor deployment in an agricultural field, remotely uploading measurements without interfering with farming operations. The current hardware revision (Soil Power Sensor was originally designed for monitoring power output of microbial fuel cells using high fidelity voltage and current measurement channels, as well as auxiliary sensors such as the SDI-12 TEROS-21 soil moisture sensor. The primary activities of this project will involve low-level firmware design and implementation, but may also incorporate hardware design revisions if necessary. We are looking to expand functionality to other external sensors, as well as optimize for power consumption, via significant firmware design activities.

Long-range, low-power wireless communication is achieved through a LoRa capable STM32 microcontroller with in-lab experiments using an ESP32 microcontroller to enable the simpler WiFi interface. Both wireless interfaces communicate upload measurements to our data visualization dashboard, ENTS I. The combined goal across both of these projects is to create a system that enables researchers to test and evaluate novel sensing solutions. We are looking to make the device usable to a wide range of researchers which may not have a background in electronics, so are interested in design activities that enhance user friendliness.

In total there will be 2-4 people working on the hardware with progress being tracked on GitHub. Broader project planning is tracked through a Jira board. We intend to have weekly meetings to provide updates on current issue progress along with assigning tasks. Please reach out to John Madden if there are any questions or specific ideas for the project.

Below is a list of project ideas that would be beneficial to the ENTS project. You are not limited to the following projects, and encourage new ideas that enhance the platform:

Backup logging via SD card
I2C multiplexing for multiple of the same sensors
Batch sensor measurement uploading

Chameleon Trovi Redesign

Wed, 21 Feb 2024 13:43:55 -0600

Trovi on Chameleon is an open-source service designed to significantly enhance the practical reproducibility of computer science research. By allowing Chameleon users to upload, share, and access packaged experiments and other research artifacts, Trovi aims to streamline the process of replicating and building upon existing studies. This capability is crucial in the scientific community, where the ability to accurately reproduce research results is as fundamental to validating, critiquing, and extending scientific findings as reading papers. The importance of Trovi lies in its potential to serve as a centralized hub that facilitates the exchange of valuable research outputs, promotes transparency, and fosters collaboration among researchers. By improving the ease with which experiments can be replicated and data can be shared, Trovi supports the advancement of knowledge and innovation in the field of computer science, making it an essential tool for researchers seeking to contribute to the development of reproducible and robust scientific research.

This project will focus on the evolution of Trovi. It will aim to enhance Trovi as a tool to advance practical reproducibility in CS research. Students will evaluate the most important use cases and enabling features necessary to enhance Trovi’s functionality and user experience. With these design insights, students will then create a robust interface that allows researchers to integrate experiment code and data easily as packaged artifacts, similar to the user-friendly design of Google Colab, and build off other users’ artifacts to create novel experiments, similar to the design of GitHub. Furthermore, students will create comprehensive documentation with valuable insights into what works well and what requires improvement, creating a dynamic feedback loop to guide the ongoing redesign process. Lastly, students will actively participate in designing webinars, creating and posting video tutorials, and organizing academic events at the University of Chicago to showcase the work on Trovi. This multifaceted project ensures a well-rounded experience and fosters a collaborative learning environment.

Each of the project ideas below focuses on a different aspect of the overall goal to enhance Trovi as a tool for advancing practical reproducibility in CS research. They are designed to offer a comprehensive approach, from technical development to community engagement, ensuring a well-rounded enhancement of the service.

Topics: User Interface Design User Experience Web Development
Skills: HTML/CSS, JavaScript, UX design principles
Difficulty: Moderate to Hard
Size: Medium to Large
Mentors: Mark Powers
Tasks:
- Conduct user research to understand the needs and pain points of current and potential Trovi users.
- Design wireframes and prototypes that incorporate user feedback and aim to simplify the process of uploading, sharing, and reusing research artifacts.
- Implement the frontend redesign using a modern web framework to ensure responsiveness and ease of use.

Packaged Artifacts Integration System

Topics: Cloud Computing Data Management Web APIs
Skills: Python, RESTful APIs, Docker, Git
Difficulty: Hard
Size: Large
Mentors: Mark Powers
Tasks:
- Develop a system that allows users to easily package and upload their experimental code and data to Trovi.
- Create a standardized format or set of guidelines for packaging experiments to ensure consistency and ease of use.
- Implement API endpoints that enable automated uploads, downloads, and integration with other tools like GitHub or Zenodo.
- Test the system with real-world experiments to ensure reliability and ease of integration.

Community Engagement and Educational Materials

Topics: Educational Technology Community Building Content Creation
Skills: Video Editing, Public Speaking, Event Planning
Difficulty: Moderate
Size: Medium
Mentors: Mark Powers
Tasks:
- Design and organize webinars that introduce Trovi and its new features to the research community.
- Create engaging video tutorials that guide users through the process of using Trovi for their research needs.
- Develop comprehensive documentation that covers both basic and advanced use cases, troubleshooting, and tips for effective collaboration using Trovi.
- Organize academic events, such as workshops or hackathons, that encourage the use of Trovi for collaborative research projects.

Feedback Loop and Continuous Improvement System

Topics: Software Engineering Data Analysis User Feedback
Skills: Python, SQL, Data Visualization, Web Development
Difficulty: Moderate
Size: Medium
Mentors: Mark Powers
Tasks:
- Implement a system within Trovi for collecting, storing, and analyzing user feedback and usage data.
- Develop dashboards that visualize feedback trends and identify areas for improvement.
- Create mechanisms for users to easily report bugs, request features, and offer suggestions for the platform.
- Use the collected data to prioritize development efforts and continuously update the platform based on user needs and feedback.

Open Sensing Platform (OSP)

Mon, 05 Feb 2024 00:00:00 +0000

Open Sensing Platform I: Software to enable large scale outdoor sensor networks

Topics: Data Visualization, Backend, Web Development, UI/UX, Analytics
Skills:
- Required: React, Javascript, Python, SQL, Git
- Nice to have: Flask, Docker, CI/CD, AWS, Authentication
Difficulty: Medium
Size: Large (350 hours)
Mentors: Colleen Josephson, John Madden, Aaron Wu

Open Sensing Platform (OSP) is a new initiative expanding from our prior project DirtViz, a data visualization web platform for monitoring microbial fuel cell sensors (see GitHub). The mission is to scale up the current platform to support other researchers or citizen scientists in integrating their novel sensing hardware or microbial fuel cell sensors for monitoring and data analysis. Examples of the types of sensors currently deployed are sensors measuring soil moisture, temperature, current, and voltage in outdoor settings. The focus of the software half of the project involves building upon our existing visualization web platform, and adding additional features to support the mission. A live version of the website is available here.

Deliverables:
- Create a system for remote collaborators/citizen scientists to set up their sensors and upload securely, eg. designing user flow to create sensors
- Craft an intuitive navigation system so that data from deployment sites around the world can be easily viewed, eg. designing experience/system to locate deployment sites.
- Refine our web-based visualization tools to add additional features for users to analyze collected data, eg. lazy loading out-of-range data or caching queried data.
- Document the tool thoroughly for future maintenance

Open Sensing Platform II: Hardware to enable large scale outdoor sensor networks

Topics: Embedded system, wireless communication, low-power remote sensing
Skills:
- Required: C/C++, Git, Github, Platformio
- Nice to have: PCB design and debugging experience, STM32 HAL, ESP32 Arduino, protobuf, python, knowledge of standard communication protocols (I2C, SPI, and UART)
Difficulty: Hard
Size: Large (350 hours)
Mentors: Colleen Josephson, John Madden, Stephen Taylor

The Open Sensing Platform hardware aims to be a general purpose hardware platform for outdoor sensing (e.g. agriculture, ecological monitoring, etc.). The typical use case involves a sensor deployment in an agricultural field, remotely uploading measurements without interfering with farming operations. The current hardware revision (Soil Power Sensor) was originally designed for monitoring power output of microbial fuel cells using high fidelity voltage and current measurement channels, as well as auxiliary sensors such as the SDI-12 TEROS-12 soil moisture sensor. The primary activities of this project will involve low-level firmware design and implementation, but may also incorporate hardware design revisions if necessary. We are looking to expand functionality to other external sensors, as well as optimize for power consumption, via significant firmware design activities.

Long-range, low-power wireless communication is achieved through a LoRa capable STM32 microcontroller with in-lab experiments using an ESP32 microcontroller to enable the simpler WiFi interface. Both wireless interfaces communicate upload measurements to our data visualization dashboard, Open Sensing Platform I. The combined goal across both of these projects is to create a system that enables researchers to test and evaluate novel sensing solutions. We are looking to make the device usable to a wide range of researchers which may not have a background in electronics, so are interested in design activities that enhance user friendliness.

Deliverables: Contribution via commits to the GitHub repository with documentation on completed work. A changelog of contributions to the firmware.

Polyphorm / PolyPhy

Mon, 07 Nov 2022 10:15:56 -0700

Polyphorm is an agent-based system for reconstructing and visualizing optimal transport networks defined over sparse data. Rooted in astronomy and inspired by nature, we have used Polyphorm to reconstruct the Cosmic web structure, but also to discover network-like patterns in natural language data. You can find more details about our research here. Under the hood, Polyphorm uses a richer 3D scalar field representation of the reconstructed network, instead of a discrete representation like a graph or a mesh.

PolyPhy will be a Python-based redesigned version of Polyphorm, currently in the beginning of its development cycle. PolyPhy will be a multi-platform toolkit meant for a wide audience across different disciplines: astronomers, neuroscientists, data scientists and even artists and designers. All of the offered projects focus on PolyPhy, with a variety of topics including design, coding, and even research. Ultimately, PolyPhy will become a tool for discovering connections between different disciplines by creating quantitatively comparable structural analytics.

Develop website for PolyPhy

Topics: Web Development Dynamic Updates UX
Skills: web development experience, good communicator, (HTML/CSS), (Javascript)
Difficulty: Moderate
Size: Medium or large (175 or 350 hours)
Mentors: Oskar Elek

Develop a clean and welcoming website for the project. The organization needs to reflect the needs of PolyPhy users, but also provide a convenient entry point for interested project contributors. No excessive pop-ups or webjunk.

Specific tasks:

Work with mentors on understanding the context of the project.
Port the contents of the repository page to a dedicated website.
Design the structure of the website according to best OS practices.
Work with the visual designer (see below) in creating a coherent and organic presentation.
Interactively link important metrics from the project dev environment as well as documentation.

Design visual experience for PolyPhy’s website and presentations

Topics: Design Art UX
Skills: vector and bitmap drawing, sense for spatial symmetry and framing, (interactive content creation), (animation)
Difficulty: Moderate
Size: Medium (175 hours)
Mentors: Oskar Elek

Develop visual content for the project using its main themes: nature-inspired computation, biomimetics, interconnected structures. Aid in designing visual structure of the website as well as other public-facing artifacts.

Specific tasks:

Work with mentors on understanding the context of the project.
Design imagery and other graphical elements to visually (re-)present PolyPhy.
Work with the technical writer (see below) in designing a coherent story.
Work with the web developer (see above) in creating a coherent and organic presentation.

Write PolyPhy’s technical story and content

Topics: Writing Documentation Storytelling
Skills: experienced writing structured text over 10 pages, well read, (technical or scientific education)
Difficulty: Moderate
Size: Medium or Large (175 or 350 hours)
Mentors: Oskar Elek

Integral to PolyPhy’s presentation is a story that the users and the project contributors can relate to. The objective is to develop the verbal part of that story, as well as major portions of technical documentation that matches it. The difficulty of the project is scalable.

Specific tasks:

Work with mentors on understanding the context of the project.
Write different pages of the project website.
Work with mentors to improve project’s written community practices (diversity, communication).
Write and edit narrative and explanatory parts of PolyPhy’s documentation.
Work with the visual designer (see above) in designing a coherent story.

Video tutorials and presentation for PolyPhy

Topics: Video Presentation Tutorials Didactics
Skills: video editing, creating educational content, communication, (native or fluent in another language)
Difficulty: Easy-Moderate
Size: Medium or Large (175 or 350 hours)
Mentors: Oskar Elek, Drew Ehrlich

Create a public face for PolyPhy that reflects its history, context, and teaches its functionality to users in different degrees of familiarity.

Specific tasks:

Work with mentors on understanding the context and history of the project.
Interview diverse project contributors.
Create a video documenting PolyPhy’s history, with roots in astronomy, complex systems, fractals.
Create a set of tutorial videos for starting and intermediate PolyPhy users.
Create an accessible template for future tutorials.

Implement heterogeneous data I/O ops

Topics: I/O Operations File Conversion Numerics Testing
Skills: Python, experience working with scientific or statistical data, good debugging skills
Difficulty: Moderate-Challenging
Size: Medium or Large (175 or 350 hours)
Mentors: Oskar Elek, Anisha Goel

By default, PolyPhy operates with an unordered set of points as an input and scalar fields (float ndarrays) as an output, but others are applicable as well. Design and implement interfaces to load and export different data formats (CSV, OBJ, HDF5, FITS…) and modalities (points, meshes, density fields). The difficulty of the project can be scaled based on contributor’s interest.

Specific tasks:

Research which modalities are used by members of the target communities.
Implement modular loaders for the inputs and an interface to PolyPhy core.
Implement exporters for simulation datasets and visualization captures.
Write testing code for the above.
Integrate external packages as necessary.

Setup CI/CD for PolyPhy

Topics: Continuous Integration Continuous Deployment DevOps
Skills: experience with CI/CD, GitHub, Python package deployment
Difficulty: Moderate
Size: Large (350 hours)
Mentors: Oskar Elek, Anisha Goel

The objective is to setup a CI/CD pipeline that automates the build testing and deployment of the software. The resulting process needs to be robust to contributor errors and work in the distributed conditions of a diverse contributor base.

Specific tasks:

Automate continuous building, testing, merging and deployment for PolyPhy in GitHub.
Publish the CI/CD metrics and build assets to the project webpage.
Work with other contributors in educating them about the best practices of using the developed CI/CD pipeline.
Add support for automated packaging using common management systems (pip, Anaconda).

Refine PolyPhy’s UI and develop new functional elements

Topics: UI/UX Visual Experience
Skills: Python programming, UI/UX development experience, (knowledge of graphics)
Difficulty: Moderate
Size: Large (350 hours)
Mentors: Oskar Elek, David Abramov

The key feature of PolyPhy is its interactivity. By interacting with the underlying simulation model, the user can adjust its parameters in real time and respond to its behavior. For instance, an astrophysics expert can load a dataset of 100k galaxies and reconstruct the large-scale structure of the intergalactic medium. A responsive UI combined with real-time visualization allows them to judge the fidelity of the reconstruction and make necessary changes.

Specific tasks:

Implement a platform-agnostic UI to house PolyPhy’s main rendering context as well as secondary analytics.
Work with the visualization developer (see below) to integrate the rendering functionality.
Optimize to UI’s performance.
Test the implementation on different OS platforms.

Create new data visualization regimes

Topics: Interactive Visualization Data Analytics 3D Rendering
Skills: basic graphics theory and math, Python, GPU programming, (previous experience visualizing novel datasets)
Difficulty: Challenging
Size: Large (350 hours)
Mentors: Oskar Elek, David Abramov

Data visualization is one of the core components of PolyPhy, as it provides a real-time overview of the underlying MCPM simulation. Through the feedback provided by the visualization, PolyPhy users can adjust the simulation model and make new findings about the dataset. Various operations over the reconstructed data (e.g. spatial searching) as well as important statistical summaries also benefit from clear visual presentation.

Specific tasks:

Develop novel ways of visualizing scientific data in PolyPhy.
Work with diverse data modalities - point clouds, graphs, scalar and vector fields.
Add support for visualizing metadata, such as annotations and labels.
Create UI elements for plotting statistical summaries computed in real-time.

Discrete graph extraction from simulated scalar fields

Topics: Graph Theory Data Science
Skills: good understanding of discrete math and graph theory, Python, (GPU programming)
Difficulty: Challenging
Size: Large (350 hours)
Mentors: Oskar Elek, Farhanul Hasan

Develop a custom method for graph extraction from scalar field data produced by PolyPhy. Because PolyPhy typically produces network-like structures, representing these structures as weighted discrete graphs is very useful for efficiently navigating the data. The most important property of this abstracted representation is that it preserves the topology of the base scalar field by navigating the 1D ridges of the scalar field.

Specific tasks:

Become familiar with different algorithms for graph growing and skeleton extraction.
Implement the most suitable method in PolyPhy, interpreting the source scalar field as a throughput (transport) network. The weights of the resulting graph need to reflect the source throughputs between the respective node locations.
Implement common graph operations, e.g. hierarchical clustering and reduction, shortest path between two nodes, range queries.
Optimize the runtime of the implemented methods.
Work with the visualization developer (see above) to visualize the resulting graphs.

DirtViz 2.0 (2023)

Mon, 07 Feb 2022 00:00:00 +0000

DirtViz is a project to visualize data collected from sensors deployed in sensor networks. We have deployed a number of sensors measuring qualities like soil moisture, temperature, current and voltage in outdoor settings. This project involves extending our existing visualization stack, DirtViz 1.0 (see github), and expanding it to version 2.0. The project goal is to create a fully-fledged dataviz tool tailored to the types of data collected from embedded systems sensor networks.

Visualize Sensor Data

Topics: Data Visualization, Analytics
Skills: javascript, python, bash, webservers, git, embedded systems
Difficulty: Easy/Moderate
Size: Large, 350 hours
Mentors: Colleen Josephson, Sonia Naderi, Stephen Taylor, John Madden

Specific tasks:

Refine our web-based visualization tools to easily allow users to zoom in on date ranges, change axes, etc.
Create a system for remote collaborators/citizen scientists to upload their own data in a secure manner
Craft an intuitive navigation system so that data from deployment sites around the world can be easily viewed
Document the tool thoroughly for future maintenance
If interested, we are also open to you investigating correlations between different data streams and doing self-directed data analysis

website design | UCSC OSPO

Environmental NeTworked Sensor (ENTS)

ENTS I: Usability improvements for visualization dashboard

ENTS II: Migration to TockOS

Develop a clean and intuitive web-based interface for WildberryEye

WildBerryEye

Develop web-based user interface

Environmental NeTworked Sensor (ENTS)

ENTS I: Web portal for large-scale sensor networks

ENTS II: Hardware to for large-scale field sensor networks

Chameleon Trovi Redesign

User Interface Redesign for Experiment Artifacts Sharing

Packaged Artifacts Integration System

Community Engagement and Educational Materials

Feedback Loop and Continuous Improvement System

Open Sensing Platform (OSP)

Open Sensing Platform I: Software to enable large scale outdoor sensor networks

Open Sensing Platform II: Hardware to enable large scale outdoor sensor networks

Polyphorm / PolyPhy

Develop website for PolyPhy

Design visual experience for PolyPhy’s website and presentations

Write PolyPhy’s technical story and content

Video tutorials and presentation for PolyPhy

Implement heterogeneous data I/O ops

Setup CI/CD for PolyPhy

Refine PolyPhy’s UI and develop new functional elements

Create new data visualization regimes

Discrete graph extraction from simulated scalar fields

DirtViz 2.0 (2023)

Visualize Sensor Data