post Ford Fiesta, masina twitterista si alte idei de viitor

May 14th, 2010

Insemnare despre: internet — clickio @ 9:59 am

Conceptul de masina conectata e urmatoarea senzatie pe care o pregatesc producatorii auto. De la masina in care multimedia e la putere, fiecare pasager are ecran si tastatura, si masina e conectata la internet pentru a beneficia de tot continutul posibil, la masina care daca tot detecteaza si detine informatii in timp real, le trimite si pe Twitter :)

Ford testeaza in prezent un set de aplicatii experimentale care permit comunicarea masina-masina si masina-om, si una din ele include o masina care publica automat pe Twitter tot felul de mesaje, de la raportul ultimului traseu, la modul in care “se simte”: evident, se simte prost in blocaje si bine cand are drumul liber :) Masina foloseste si serviciul de geolocalizare Foursquare, pentru a arata pe unde a ajuns, si teoretic face si poze pentru a arata conditiile care declanseaza “starile” pe care le raporteaza.

“For example, if one assumes that a happy car is one that’s zipping along an open road or negotiating tight curves,” explains Giuli, “the powertrain sensors – engine rpm, speed, steering inputs, g-loads, that sort of thing – can indicate to the car that it’s in one of those fun situations, and the car can then indicate that with a tweet or blog post. Similarly, if it’s at zero mph with the wipers on, the car might decide it’s sitting in traffic in the rain and send a sad tweet. Either way, we wanted to allow the car to become a blogger.”

AJ will also be able to indicate via GPS trace the roads on which it’s driving when it feels certain ways, and the system will also allow it to take a photo to show other drivers – and perhaps, someday, other cars – the conditions that trigger its opinions.

@AJtheFiesta, ca asa o cheama pe masina nazdravana, e parte dintr-un proiect mai amplu al Ford, numit “Ford’s American Journey 2.0 ” si care a provocat studenti de la Universitatea din Michigan sa genereze idei despre cum ar putea arata viitoarea “masina sociala”

Iata ideile finaliste:

  • Caravan Track was judged the winning app. The software allows clusters of vehicles traveling together to track each other along the journey. After identifying a route on a main website, users can join to see fellow travelers; view vehicle telemetry including fuel level and speed; track each vehicle; map routes; send alerts about stops along the way; and send text notifications about road conditions and hazards via a multiple choice interface that eliminates the need to type. Team members include John Ciccone, Collin Hockey, Sang Park and Joe Phillips.
  • Fuel Tracker provides drivers with real-time feedback about fuel economy and driving habits based on past drivers on a specific route. App users upload their results for different road segments, allowing users to compare details, compete for top fuel economy and share suggestions for improving mileage along specific routes. Team members include Paul Coldren, Amy Kuo, Petch Wannissorn and Clayton Willey.(un proiect similar are si Nissan)
  • The GreenRide Challenge provides a collaborative ride-sharing system, attempting to connect drivers with potential carpool passengers in an effort to reduce greenhouse gas emissions. The app is connected through Facebook, matching friends who need rides with destinations entered by the driver – and also allowing the driver to invite friends to ride. Points would be awarded for ride-sharing, providing for a possible sponsored reward component. Team members include Scott Dang, Nate Hill, Raphael Jarrouj and Bryan Summersett.
  • Listen. Speak. Rate. Share. provides users in-car audio reviews for various points of interest, and also allows drivers to share their thoughts on visited locations, connecting through Facebook, Twitter, LinkedIn and other popular social media sites. Team members include James Di, Yi-wei Ma, Alok Talekar and Xiaowen Zhang.
  • NostraMap collects data about road and traffic conditions, giving drivers advance notice about accidents, construction, poor surfaces and other hazards. The app relies on crowd-sourcing: When a user encounters a situation, he or she draws a single character on the map display (A for accident, C for construction, etc.), which is then updated for all users to see. Team members include Murtuza Boxwala, Nader Jawad, Justin Taseski and Sui Yan.
  • Points-of-Interest uses a dynamic recommendation system to point drivers toward locations and businesses that match their interests but that they may not have otherwise visited. The system uses a complex algorithm to learn a driver’s tastes and interests over time, allowing it to provide more tailored recommendations and learn the tastes of users with similar interests. Team members include Ryan James, Brad Rubin, Dhritiman Sagar and Weihua Wang.

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