**Notiefy** is a currency detection app for the visually impaired which had a really basic UI, so that the app can be easily and quickly used. The app opens up with a camera with a large button in the bottom-middle for the blind person to click the image easily, and the application would process the image and with the help of artificial intelligence, it would classify what currency-note it is with the help of a computer-generated audio. It also says the total amount of money it has been shown to the camera because the speaker had mentioned that also as a difficulty, when the person has a bunch notes to count. The app, time being works only for Indian currency notes.

1. CURRENCY RECOGNITION SYSTEM
FOR VISUALLY IMPAIRED
Ben Sam Sabu 17
C J Peter 18
Govind B Chandran 22
Mannu Thomas 35

2. ABSTRACT
The main objective of our program is to detect the value a
currency note holds. We made it for the visually impaired to
recognise these currency notes as they could be easily cheated
by other people.

3. PROBLEM STATEMENT
The existing apps for currency recognition for the
visually-impaired have really complicated user interface and people are better off
without them. Also asking to other people during this covid-19 outbreak is highly
risky, excluding the risk that the "other" person here was a part of the "cheater's" alibi.
Hence we decided to build a mobile application which was easy to use and fast and
accurate too, so that they can be more safe out in public and have a better life in the
world.

4. Related works
Technology Advantages Disadvantages
Cash Reader
(Mobile Application)
Identification,Voice
Assisted Output
Complicated User Interface,
Relatively low accuracy
MANI
(Mobile Application)
Good accuracy,
Identification,
Voice Assisted Output
Extremely complicated
Interface

5. Implementation Diagram

6. Modules Used
1. Currency Detection Unit - To detect the currency note given by
the user.
2. Voice Assistance - The predicted output is given to the user as
audio.
3. Currency Counter - To count the total amount of a set of
currencies given by the user.

7. Softwares used
1. Android Studio
2. Jupyter Notebook [Anaconda]
3. Google Teachable Machine
Hardwares Used
1. Android Device

8. Application Interface

9. REFERENCES
Vrushali Sindhikar, Snehal Saraf, Ankita Sonawane, and Shamali Thakare, "Currency
Recognition System For Visually
Impaired," International Journal Of Advance Research And Innovative Ideas In Education, vol.
3, no. 2, pp. 3264-3269, Mar- App 2017. [Online]. Available:
http://ijariie.com/AdminUploadPdf/Currency_Recognition_System
_For_Visually_Impaired_ijariie4599.pdf [Accessed : ].