I'm currently doing my final year project. The end product of this project is to develop an Android application that can be used by an individual to track the amount of carbon gas emitted through daily activities and consumption. I'm having trouble in searching and understanding the method use for calculation. Anyone can explain?
You will most likely need to get the user to input their daily food waste, etc and use a formula to calculate it. A quick search on google brought me to https://www3.epa.gov/carbon-footprint-calculator/ which has an excelsheet with the various formulas you can download on that page.
As for how the formula or its constants are derived, I have no clue myself.
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I am working on scanning bill receipt to get important data from it like restaurant name, date, total price, tax etc. But not getting any appropriate solution. Take reference from play store app name 'Receipt Bank'
Similar to what other's have pointed out, you will need to use a technique called OCR (Optical Character Recognition) in order to process the receipts and convert that to usable text. There are several good libraries already out there, choosing one will just depend on your constraints (time, money, etc). I wouldn't recommend reinventing the wheel here and attempting your own OCR library.
See this answer for a more detailed list of libraries to you.
For the lazy, here are the recommendations in the link.
If you have plenty of time but zero budget - your choice is Tesseract. It is definitely the best among open source
If you have a small budget to spend and you only need run this recognition once - Cloud OCR API service would be your best choice. It is based on leading commercial grade OCR engine and offers quite affordable per-project prices. Disclaimer: I work for ABBYY
In case you will need to run this recognition as ongoing process forever, then you may think that it is economically more efficient to purchase dedicated conversion software, for example this one, it has API and can be called from Java too. But there are actually a lot of alternatives, if you are prepared to invest some budget in licensing.
Once you have the library integrated, it will be up to you to write the logic for adding the values returned by the OCR library and showing them to your user. Until you choose which OCR library to use, I cannot give you any more insight into how to do this, because it highly depends on the output format of the library.
if you mean scanning Barcode using Android camera? I am going to give you what I know about your question
I suggest the following improvements to process
Carete database table contains all information you want witin your bill with primary key which will be the Barcode scanned by camera
when you scan Barcode you wil actually scan the primary key for the information about bill like (restaurant name,.. etc)
Small query will get you all information you need in bill
As part of my final project for a 1 year software development course i am required to implement a knn project which predicts the outcome of football matches in an android app.
I built a mysql database on an online hosting site (byethost) using predictors:
difference in average goals per game
diff in average points per game
diff in average goals conceded per game
outcome
My tutor recommended k should equal 100 and that a significant data set be constructed (over 1000 results)
From here on i am lost as to how i should approach the problem at hand. Can anyone give any further guidance as to how to tackle the problem.
All advice is welcomed.
This is too long for a comment.
K-NN could be used as part of the solution. However, it is an undirected data mining algorithm, meaning specifically that it doesn't generate expected outcomes. That means that K-NN is not appropriate as the only technique used for a final project that depends on prediction.
I am concerned about any year-long course that makes such a recommendation. The difference between directed and undirected algorithms is pretty fundamental.
I'm developing an android application which recognizing accelerometer gesture. For now I'm just utilizing dynamic time warping to get the smallest distance between input gesture and about 200 unique gesture data in database. My application looping through the data and compare the input gesture with gesture data in the database one by one. It can find the smallest distance and recognizing the gesture for average in 5 second. The problem is can i speed up recognition time maybe for half second or less? Do I have to use classfication method like KNN and combine it with dtw method? an example or references will be apreciated..
What you are currently doing is a 1NN. In other words, you are already running a simplest possible KNN method. with K=1. Changing K won't speed up anything, it can only change the quality of the result. To speed up the process you can think about using two approaches:
Using some indexing methods, which will reduce the computational complexity of your distance based search. This problem is called Nearest Neighbout Search (NNS), and even wikipedia provides quite a lot of information regarding its speed ups;
Using completely different classification method, which build a much simplier model (possibly SVM or even some decision tree - it depends on your actual data).
My intuition is that Locally Sensitive Hashing can be quite easily applicable. For instance you could design them by picking K points randomly and checking if the time series isn't too "far" away.
I would go into more details on that idea, but instead I found this paper : http://dtai.cs.kuleuven.be/events/MLSA13/papers/mlsa13_submission_13.pdf , and it seems to be using much simpler LHS function.
So this is one way out, hope it works out. You can also implement an easy classifier and accept its answer if it is very certain about the gesture (I would recommend SVM here as in the answer above), and if it is close to the boundary decision look for the closest neighbour.
you can do DTW at 10,000 hz, even on a phone, see this vid
http://www.youtube.com/watch?v=d_qLzMMuVQg
eamonn
I'm thinking of doing an image processing app for android as my senior year project. The basic functionality I'd like is for the user to be able to take a photo from the camera and then try to match it to certain preexisting images in the database.
I'll be using it for distinct objects, not objects with varying characteristics like pen, car, etc. Rather objects like maybe the Eiffel tower. The app should be able to recognize an Eiffel tower based on the photo taken from the camera and comparing it to an already existing pic of the Eiffel tower.
Is this project feasible in a 6 month time frame or is it feasible at all?
What APIs does android provide to get this job done ?
Thank you
I suggest using a neural network, and than training it for the objects you want to recognize.
Also, you should try implement pattern recognition natively for better performance. Still, I'm not confident that it would work well in terms of recognition mistakes and fast execution. Also, you would need large training datasets for every object you want to recognize, pictures from different angles, taken during day and night, in different weather occasions... Recognition performance could be improved if you take into account gps location from which is picture taken (Eiffel tower surely is not visible from London). If you want to make this to work it would take a tremendous amount of effort.
I have done the same thing as a project in 3 months or so. There is not Andriod API. But you can build an application for it. In my project I send the snapshot image to a server to do that match, the server have a database for image build with "bag of words" model and using SIFT/SURF as feature extraction algorithms. The server will reply with information to the mobile client as need. There is a tutorial how to build the a similar thing here
I am developing Android application for the company. They want me to create digital newspaper that would:
Display list of headlines for each category/subcategory
Will have 4-6 categories and 4-8 subcategories for each category
Display article with text and images,
Play podcast,
Save downloaded articles/headlines in db
They already have the web-service almost adopted for this app.
This app will be quite similar to: TechnologyReview or CNET News (but the article will be larger)
I have estimated this project for 160 hours of development. That doesn't include design but includes design implementation.
I would love to hear your opinion on this estimate. Do you think 160h is too short or too long? How much I should charge for this project or 1 hour of development(more or less of course)? I am living in London, UK
I need this estimation by the end of today so I will be really grateful for fast replies.
If you have a similar project, or some similar code files you can bunch together into a folder, you can simply run ProjectCodeMeter over it and get a ballpark cost estimation that will point you in the right direction.
Good luck!
The way to do estimates is to break down the project into each component and estimate each of those. Trying to ballpark one number is inevitably worse than ballparking a breakdown. This also helps you get better on each estimate in the future because you know which estimates made sense and which were wrong.