Olive Fruit Fly Detection and Monitoring Solution Olive fruit fly poses a severe economic threat to olive growers throughout the world (Greece, Spain, France, Italy, Turkey, California). According to University of California Agriculture & Natural Resources IPM Online (http://www.ipm.ucdavis.edu/PMG/PESTNOTES/pn74112.html) the larvae of the olive fruit fly feed inside the fruit, destroying the pulp and allowing the entry of secondary bacteria and fungi that rot the fruit and degrade the quality of the oil. Feeding damage can cause premature fruit drop and reduce fruit quality for both table olive and olive oil production. Large numbers of rotting fruit on the ground can create an unwelcome mess, especially in landscaped situations. Olive fruit fly threat has a high social-economic impact i.e. according to European Union report http://ec.europa.eu/environment/life/publications/lifepublications/lifefocus/documents/oliveoil.pdf in Europe the olives area of production is around 4,8 Million (ha) and the sector only in Spain creates 7500 full-time jobs. Currently olive fruit detection and monitoring is done with the use of McPhail-type traps or yellow sticky tapes with pheromone either chemical or biological (ECO TRAP) attractive to male flies. According to EU guidelines 2-3 monitoring traps should be present on 10,000 square metres and monitoring of the traps should be done every 2 days. Currently there is no monitoring system capable to distribute the monitoring data in real time to allow quick identification of an olive fruit fly population. Our hack idea is to utilize modern technologies Machine to Machine, Resin.io, Raspberry Pi, Collective Intelligence, Image Processing, Social Networking and Cloud computing with the goal to improve olive fruit fly detection and monitoring system. See More here : http://goo.gl/UWjPPu using #Raspberry Pi #Node.js #Express #Mongo-DB #mongoose #Angular.js #Handlebars #Coffeescript #Bower #npom #Nitrous.io #resin.io #docker #android

1. Athens Location
Sponsored by coLab
Raspberry-Pi & Camera
Sponsored by resin.io
Olive Fruit Fly
Detection and Monitoring Solution

2. High Level Architecture Friday 7/2/2014 19:00 CET
B
B1
Agronomists
A
OpenData
Data Hackers
Local Farmer
B3
Other Farmers
Biological Olive Fly Protection
Spread via Drone
B2

3. Thomas Porter
Robin Venneman
Sotiris Salloumis
Staacy Cannon
Daryl Lukas
Global Online Team
Thanks to Staacy Cannon for her support from Geeklist without her this team would not exist
Thanks to Resin.io team at Athens Offices for their support
Thanks to CoLab Workspace and Spiros Kapetanakis for hosting the event in Athens
Thanks to family and friends supporting during this 48hous hackathon

4. Raspberry Pi
WiFi
Camera
Solar Powered : http://reviews.cnet.co.uk/desktops/how-tomake-a-raspberry-pi-solar-powered-ftp-server-50009923/
Type B (Collector)

5. Collector

6. High-Res Image
Longitude – Latitude
Timestamp
Farm Id
Camera Id
..
API
Nitrous.io
Frontend
Farmer
Agronomist

9. Summary
Collector
Frontend
• Collector
• Frontend
• Hardware
• Raspberry Pi + Camera module
• McPhail Traps
• Customizing to attach Raspberry Pi +
Camera
• Software
• Raspberry Bash Script  resin.io
• Backend
• API for collector gathering
• API for frontend
• One Page App
• Register
• Sign-in
• Angular-Js Google Maps status
• Android
• Farmer Apps
• Architecture
• Web 2.0 – API powered

10. Full of Geek Technologies
Frontend
Collector
• Node.js / Express
• Mongo-DB / mongoose
• Angular.js
• Handlebars
• Coffeescript
• Bower / npm
• Nitrous.io
• Raspberry-Pi + Camer
• resin.io
• Docker
• Android