Project

# Title Team Members TA Documents Sponsor
22 Smart Drone Delivery Improvement
Rahul Joshi
Raymond Hoagland
Sachin Weerasooriya
Luke Wendt appendix0.docx
design_document0.pdf
final_paper0.pdf
other0.pdf
presentation0.pptx
proposal0.pdf
When you order a package that is shipped via ground, it is either left at your door or you must be present to sign off on the package. Services like Amazon PrimeAir look to speed up delivery time with drone shipping, which claims to be able to come to your door in 30 minutes. If you look at Video 2 in this link, you will see that the shipment is loaded and the drone takes off, converts to a plane, flies to the vicinity of the landing local, converts back to a drone, and lands on a marker put out by the recipient. This drone then deposits the package and returns to the factory for its next package. Here lies a major flaw; in the event that something valuable is being shipped, it would be desirable for their to be a confirmation that someone is available to pickup the package that is being delivered.



This is where we step in. The problem we want to address is we will assume that the drone is in the area of the delivery spot. We will use image processing to ID the user specified landing spot. The key difference will be: instead of landing, the drone will notify the owner that the package is ready for pickup and hover above the landing spot for a fixed amount of time. The drone will then wait for a confirmation from the user that it is safe to drop off the package. If this message isn't received after a set amount of time, the drone will return to the warehouse with the package and will try to return the package later. While the drone waits, it will constantly scan the surroundings to see if any unidentified threats are approaching the drone. If it detects a threat is too close, the drone will take off and hover at a higher elevation to protect the package contents. It will stay there until either the recipient gives the okay for delivery or until the time limit is up and the drone will return to the factory.

Hardware needed:
- A drone
- A small camera
- Digital Signal Processor (DSP) Chip
- Proportional-Integral-Derivative (PID) Controller
- Raspberry Pi
- USB wifi dongle
- Smart phone

We will use image processing to ID our landing spot and the PID controller to send the necessary feedback to the motors in order to descend the drone and lookout for potential hazards. For our prototype, will then use the raspberry pi and dongle to connect to the resident's WiFi and send a message to a smartphone app indicating the package has arrived. The drone will then wait for confirmation from the app. The mechanical mechanism to physically lower the package will be out of our scope. Rather we will have an LED or some way to indicate that the package has been dropped.

Wireless IntraNetwork

Daniel Gardner, Jeeth Suresh

Wireless IntraNetwork

Featured Project

There is a drastic lack of networking infrastructure in unstable or remote areas, where businesses don’t think they can reliably recoup the large initial cost of construction. Our goal is to bring the internet to these areas. We will use a network of extremely affordable (<$20, made possible by IoT technology) solar-powered nodes that communicate via Wi-Fi with one another and personal devices, donated through organizations such as OLPC, creating an intranet. Each node covers an area approximately 600-800ft in every direction with 4MB/s access and 16GB of cached data, saving valuable bandwidth. Internal communication applications will be provided, minimizing expensive and slow global internet connections. Several solutions exist, but all have failed due to costs of over $200/node or the lack of networking capability.

To connect to the internet at large, a more powerful “server” may be added. This server hooks into the network like other nodes, but contains a cellular connection to connect to the global internet. Any device on the network will be able to access the web via the server’s connection, effectively spreading the cost of a single cellular data plan (which is too expensive for individuals in rural areas). The server also contains a continually-updated several-terabyte cache of educational data and programs, such as Wikipedia and Project Gutenberg. This data gives students and educators high-speed access to resources. Working in harmony, these two components foster economic growth and education, while significantly reducing the costs of adding future infrastructure.