As March was approaching, I started hearing some buzz from my network of friends that attend hackathons. They were talking about this ABInBev hackathon with huge prizes and I was honestly not very interested. I’m not much of a beer fan as much as I like wine and I tend to avoid competitions that are centered around solving problems for a specific company… it makes me feel like I am being bought out? Which I probably am. Anyway, I had nothing to do that Saturday so I ended up going.
So what is this hackathon about?
Anheuser-Busch beers must pass through multiple checkpoints before they can be enjoyed by consumers. After being brewed, bottled and packaged, beers are shipped to wholesalers who then have the mission of selling them to various POCs or points of contact – think your favorite bar, restaurant, grocery or liquor store. The process to get beers from the brewery into consumers hands has improved tremendously over the years but inefficiencies still remain. Help us bring innovation to POCs and deliver your favorite beers to you as quickly as possible.
Basically, they are looking for solutions to their distribution network and guaranteeing that their beer will always be stocked in a store.
Sajal, David and I came up with a project called shelfie. It is a beer stock monitoring system which is installed in the fridge shelf of the store. The camera will detect when the beer is out of stock and alert the beer manufacturer. It also detects the type of beer such as Stella Artois, Shock Top, Elysian, etc. Another added benefit is that the system will guarantee that the beer is located in the correct placement on the shelf and competitor beers are not located on the same shelf space.
How does it work?
The system consists of a Raspberry Pi micro computer which is installed in the store shelf and a web server to receive data from the shelfie systems for analysis. First, the Raspberry Pi captures images of the top of the beer bottles. The image is processed to find all circular looking objects in the picture which should look like the top of a beer bottle. Then the circular objects that are found are compared against a classification algorithm to determine if it is a recognized beer brand. Finally, the images of the bottle tops and location data are uploaded to the web server to be displayed on a UI showing the beer arrangement on the shelf.
Check it out
The full project is located on our devpost page : Shelfie
Okay, so this is my first hackathon that I have attended in a while and I am somewhat nervous and excited. The last hackathon I attended was in college and I managed to convince Dave and Ezafat to come with me to the competition! I was sure to pack all of my stuff like an extra monitor, power strips, sleeping bag, and tons of hackable hardware. We would travel for 3 hours from NYC to Troy NY.
Create IoT hacks that solve the world’s problems: Smart Health, Smart Buildings, Smart Cities…
New WiFi and internet-enabled microcontrollers are opening the opportunity to hack together new Internet-of-Things (IoT) devices. Bringing together experts, mentors, hackers and judges, the Tech Valley Center of Gravity is hosting an IoT Hackathon 2016. Powered by AT&T, and supported by Jeff Branson of Sparkfun, the IoT Hackathon promises to be a fun and exciting event to build new devices, software and teams. Focus areas include transportation and infrastructure, health care, clean technology and consumer devices, with over $1000 in prizes to be awarded.
We wanted to create an integrated solution for fire safety among the general public. Many people die every year from smoke inhalation and carbon monoxide poisoning. The recent death of a mother and her daughter inside of a car due to carbon monoxide inspired us to come up with a solution to save lives. We wanted to come up with a system that could help fire fighters find victims quickly and prevent false alarms.
Features of the Flame Warden Alarm system
Smoke and carbon monoxide sensor
Blinking LEDs and loud buzzer sound
Additional layer of fire validation via real time video analysis
Immediate alert to the authorities and registered users of a potential threat (SMS and Email)
Locationing of people within the hazardous area
Live image of the hazard area with count of people and type of threat
How does it work
Camera / Touch Screen
Hardware Sensors (CO/Gas module/LED)
Mobile programming (iOS)
Image processing and detection (OpenCV)
Cloud Deployment (Digital Ocean)
The Raspberry Pi acts as the main unit for the fire alarm system with a smoke sensor, Carbon Monoxide sensor, camera, LED array, and speakers attached. The camera is used to count the amount of people that are in the room using OpenCV and facial recognition algorithms. The LED array is used to create a bright light to indicate that there is a fire and the speakers output a high pitch sound to alert people. When a fire is detected, the Raspberry Pi will send the data to our REST server to notify all registered devices.
Check out our project!
Here is the devpost link to our project for more info : FlameWarden