Smart Chemical Emission Navigation Tracker (SCENT)
-
Design an IoT platform with mini robotic cars equipped with gas sensors to detect gas leaks and map spatial distribution in laboratories for safe and sustainable operations.
The Smart Chemical Emission Navigation Tracker (SCENT) team focuses on developing a system for real-time monitoring and localization of chemical emissions (alcohol, carbon footprint, etc) in small-scale indoor industrial, university lab, or research and development settings. By integrating selected gas detection sensors, IoT technology, AI-driven data analytics, and engineering design principles, SCENT aims to detect and localize emissions efficiently. Unlike fixed sensor systems typically used in labs or costly mobile gas detection platforms designed for large-scale industrial environments, our solution fills a unique market gap. This project provides a cost-effective and adaptable approach, allowing for diverse sensor use across various environments. Joining SCENT offers students hands-on experience in sensor integration, IoT, data analysis, and system development, preparing them for impactful careers in environmental sustainability and emission control.
Methods & Technologies
- Chemical Emission Detection
- Simultaneous Localization and Mapping (SLAM)
- Autonomous Navigation
- Robot Operating System (ROS)
- Edge Computing (Nvidia Jetson Orin, Arduino, RaspberryPi, etc)
- Internet of Things (IoT) Technology
- Object Detection
- Deep Learning and Large Language Model (LLM)
- Data Storage and Cloud Integration
Areas of Interest
- Chemical and Biomolecular Engineering
- Civil, Urban and Environmental Engineering
- Computer Science, Data Science and AI
- Electrical and Computer Engineering
- Management of Technology
- Mechanical Engineering
- Robotics
Subteams
- Team 1: Gas Emission and Diffusion Modeling
- Team 2: Edge computing and IoT Network Development (Software)
- Team 3: Smart Cars and ROS (Hardware)
- Team 4: Project Management
Partners
- MathWorks
- Sustainable Engineering Initiative
- CBE Unit Operation Lab
Subteam 1 — Sensing & Instrumentation
What students do: Work with multiple sensor types (gas, environmental), handle sensor calibration, signal conditioning, and data quality validation.
What students gain: Hands-on experience with real analytical instrumentation that mirrors industrial practice; skills directly applicable to careers in process safety, environmental monitoring, and R&D. Students will understand how sensors behave in real-world (noisy, non-ideal) conditions — something you simply don't get in a classroom lab.
Subteam 2 — Edge Computing & IoT Software
What students do: Build the data pipeline from sensors to edge computing devices, develop dashboards for real-time monitoring, and implement data logging and cloud connectivity.
What students gain: Practical experience with embedded Linux systems, IoT protocols, and data engineering — skills in high demand across both tech and industrial sectors. Students will leave with a working portfolio project that involves real hardware, real data, and real deployment challenges.
Subteam 3 — Robotics & Hardware Integration
What students do: Design, assemble, and program mobile robotic platforms, implement autonomous navigation, and integrate sensor payloads onto robot chassis.
What students gain: End-to-end robotics development experience — from mechanical assembly to software control — using industry-relevant tools. This is the kind of hands-on system integration experience that sets candidates apart in robotics, mechatronics, and automation job interviews.
Board of Project Management & Commercialization (members selected from subteams)
What student leaders do: Coordinate cross-team deliverables, manage documentation, conduct market research, and support stakeholder communication and project reporting.
What students gain: Real exposure to how an engineering research project moves toward commercialization — including project management and budgeting, entrepreneurship in product developments, communication technical work to both technical and non-technical audiences, etc. Ideal for students interested in product manager, tech consulting, start up companies, etc.
Faculty Advisor
- Xin (Matt) Wang
- email: mattwang@nyu.edu
Multi-Semester Commitment
Students are strongly encouraged to commit to the SCENT VIP team for two or more semesters. The VIP program is designed as a multi-semester research experience where students can progressively deepen their technical skills and contributions.
Returning students often take on increased responsibility, including leadership and mentorship roles within the team, helping guide newer members and supporting long-term project development.
Who Should Apply
Students interested in the SCENT team should have a strong interest in robotics, sensing systems, data analytics, and environmental monitoring. The team welcomes students from the following majors and related backgrounds:
- Chemical Engineering and Environmental Engineering – students interested in gas sensing, emission modeling, and environmental monitoring
- Computer Science, Data Science, and AI – students interested in machine learning, data analytics, and software development
- Electrical Engineering – students interested in sensor integration, embedded systems, and IoT networks
- Mechanical Engineering and Robotics – students interested in autonomous vehicles, navigation systems, and hardware development
- Management of Technology – students interested in project coordination, product development, and technology strategy
Relevant coursework may include robotics, embedded systems, machine learning, sensor systems, environmental modeling, or related topics.