When and Where
September 13th, 2019 | 9AM - 5PM | The Edney Innovation Center | 1100 Market St. - Chattanooga, TN 37402, USA
This Year’s Theme: Testbeds
As time goes on, more and more metropolitan areas set their sights on becoming “smart cities”, and the technologies they need can’t be developed without a testbed. Chattanooga’s second annual deep-learning conference will bring together a diverse collection of talented experts in smart city testbeds. Speakers at the conference will share their knowledge on topics such as smart mobility and intelligent data structure, as well as share their insights from progress they’ve made operating testbeds of their own. In addition to the hardware itself, developers at the conference will share the software architectures they use to manage the massive amounts of data a testbed produces. Located just a few miles from Chattanooga’s own smart corridor, the 2019 Chattanooga Deep Learning Conference will be a gathering of experts in data technology fields and city influencers to come together and discuss the testbeds that will be used to shape the cities of the future.
The MLK Smart Corridor
Internet of Things
- Air Quality Sensor
- Nvidia Jetson TX2
- Raspberry Pi
- WiFi APs
- Real-time Stream APIs
- Real-time Sensor Data
- Monitoring and Analytics Dashboards
- Self-Service Application Platform
- Batch Processing on Historical Data
- Sensor Deployment Opportunities
- Self-Service Data Ingestion Infrastructure
Chattanooga’s MLK Smart Corridor does not simulate city data, it generates it. Announced in May 2019, the testbed serves as a live-urban environment for developing data-driven technologies for smart cities. Currently the testbed spans over 1.25 miles of one of the busiest streets downtown, which is full of diverse forms of traffic, from public transit to bike-shares to a heavy stream of pedestrians. The testbed is an open platform for innovators and researchers to develop their applications using a segment of a real urban environment that encompasses all of the nuances of an actual city. It is already equipped with hardware capable of collecting data on air quality, noise pollution, and traffic patterns in real time. This data can be used to improve the day-to-day life of urban citizens by decreasing public waste, improving commuter flow, and more as new use-cases are discovered and explored.
CUIP Smart City Data Challenge
The CUIP Smart Street Data Competition (CSCDC) pools together ideas for modeling datasets obtained through the use of the MLK Smart Corridor’s Testbed. This year’s competition is motivated toward finding a correlation between tracked objects and air quality. You will be given three weeks of Vehicle Events and three weeks of Air Quality data. Entrants shall submit to us a model that, using a pre-written Python wrapper script, can accurately predict the PM 2.5 air quality metric of an intersection based vision events for that same intersection. You will predict a week of PM 2.5 air quality data (June 22nd - 28th) using your model trained with the prior three weeks given. The most accurate models will win! Your model will be manually evaluated for accuracy using a week Video Events and known Air Quality data. You can access the dataset and get started by registering for CSCDC (using the button below) - we will use your email only to contact you if we have any questions. The final work must be presented as a poster (more details below) on the day of the conference - September 13th 2019.
Prize tiers will be announced soon.
Any Participant (limit 1 per group): full travel scholarship*
The dataset will be made available before the conference. Once it is available, you may download it and begin your work! More information on the dataset can be found here or through the button below. WARNING: The compressed dataset is approximately 3.23GB - please take this into account when downloading.
Participants of the competition must have a poster of the work they have accomplished ready to present during the conference’s poster session. More information on the Poster Session will be provided in the itinerary (to be announced)
* : Reimbursement may be limited if outside of the Continental United States
The MLK Smart Corridor project is deeply connected to the city around it by design. The Chattanooga Smart Community Collaborative is a partnership of 7 entities working together (City of Chattanooga, CO.LAB, The Enterprise Center, EPB, Erlanger Health Systems, Hamilton County, and The University of Tennessee at Chattanooga). These seven entities made it possible to integrate the MLK Smart Corridor directly into the heart of the city with ease. EPB, the local internet and power municipality, implements and maintains the backbone of the testbed: Chattanooga’s gigabit fiber. The University of Tennessee at Chattanooga staffs a state of the art research lab that operates on the testbed, developing ideas and technology for the city. The administration of the city enables the project to navigate major roadblocks with ease. These examples, among other collaborators, enable development for the city, motivate innovation, and align the project with the needs of the community. This collaborative framework allows for projects to have a wider scope without losing focus or productivity.
The Gig City
How did Chattanooga go from “America’s dirtiest city” to a technological powerhouse? Data. In 2009, when EPB deployed high-speed fiber throughout the entire city, Chattanooga’s main source of industry was pushed into the future. Companies and industries reliant on big data found themselves flocking to Chattanooga to utilize the gigabit infrastructure for machine learning, large scale data analysis, and more.
But there’s more to Chattanooga than just fiber! The city is full of reasons to just come visit, with activities for everyone. Take a paddle-board into the Tennessee river, try some of Chattanooga’s famous local brews, or just take a taste of some of its finest eateries. You can even walk the MLK Smart Corridor and see its seamless integration with the city for yourself. No matter who you are, you’ll never be left with nothing to do.