Sms Grocery List

Widget with Grocery List Created from Received Messages

Why?

I often found myself with messages containing shopping lists that I wanted to keep track of while heading home. My initial idea was to create an invisible app that would read incoming messages and automatically add their content to Google Keep, displaying it in a widget. However, I discovered that Google Keep does not offer an API for third-party integration. As a result, I decided to develop an app with this functionality.

What Did I Do?

The application includes a receiver that captures all new messages. Once a message is received, the app scans for predefined keywords. You can configure multiple keywords to search for in incoming messages. Additionally, the app allows you to set up reminders, which will trigger notifications at a specific time of day when at least one message has been received. These settings can be found in the app's side menu under "Settings."

The second key feature of the application is its widget. This widget displays a list of all received messages, organized by date and categorized under headings such as: Today, This Week, and This Month.

Can I Try It?

The app is available on Google Play. Since it does not require internet connectivity, users don’t need to be concerned about permissions for reading personal messages.


You can find the source code here: https://github.com/mbodis/sms_list

           


Comments

Post a Comment

Popular posts from this blog

Skate Tricks Recognition Using Gyroscope

Image
In this article, we’ll describe how to recognize skateboard tricks using a gyroscope. This sensor is already present in most smartphones, but if you’re not familiar with it, here is a description . Before we dive in, a small disclaimer: This project originated as part of a Slido hackathon with the goal of demonstrating that it’s possible to recognize skateboard tricks using a gyroscope. For simplicity, we’ll focus on recognizing just two basic tricks and won’t consider the skater’s stance on the board. We’ll break down the problem into several smaller tasks: recording the trick, storing the data, describing the trick, analyzing it, and, finally, recognizing it. Recording the Trick Let’s start with trick recording. To obtain precise data, the device with the gyroscope needs to be attached directly to the skateboard. Place it on the bottom of the board to avoid interfering with the execution of the trick. The device should also be compact and lightweight to avoid altering the board’s cen...
Read more

Play table

Image
Using proximity sensors for playing midi tones combined with LED visualization Description The goal of this project was to create a table-sized device equipped with multiple proximity sensors capable of playing MIDI tones. Each sensor is accompanied by LEDs that indicate the distance of the user's hand above the table. This interactive table can be used by one or more people simultaneously. Hardware Setup I began with a cardboard prototype to test the sensors and the underlying logic. Afterward, I ordered a custom plottered sticker with a design which was painted with bare conductive paint. I drilled holes and connected the touchboard to seven Arduino Nanos, each controlling 13 LEDs. Additionally, I incorporated two potentiometers: one for volume control and another for changing the note setup. Programming The programming task was divided into two parts: Master Program (Touchboard): Reads values from the proximity sensors and sends messages to the slave Arduinos. Sl...
Read more

Counting dice and train wagons using computer vision

Image
Computer vision exercises with preprocessing Before starting my next project, I decided to work on some computer vision exercises. Each example is based on straightforward image preprocessing techniques. No complex data structures or machine learning are involved. Dice Detection I got this idea while browsing the net and became curious about how challenging it would be to write such a script. Here’s a step-by-step breakdown of the algorithm: Movement Detection : By comparing several frames with thresholds, we can determine if there is any movement in the frame. Adding a small time buffer after the movement stops gives us more accurate information. Removing the Background : Thresholding the grayscale frame helps to remove the background, leaving us with a binary image that highlights the objects. Cropping the Objects : Using contours, we can detect and isolate the objects by cropping them. Detecting Dots : By inverting the image, the dots on the dice become more distinguish...
Read more