CRYPTO COM PANAIKINA OBLIGACIJAS IR KITAS MONETAS

ONDO KRIPTOVALIUTŲ NAUJIENOS

One of my hobbies is amateur (ham) radio. A QSO is a contact between two stations. Many hams use ARRL's Logbook of the World (LOTW) to store a log of their QSOs. I wrote QSO Viewer, a simple single page app that uses the Next.js React framework. It queries LOTW's API for a list of a user's QSOs, displays a formatted list with details, queries the gate.io app API for the location of each call sign, then charts them on a map. CALLOOK does not have location data for stations outside of the US so the value of the map is slightly limited.

I plan on improving the styling of the app and adding more features. Adding options to filter by band and mode would be a good place to start. I'd also like to add a third tab where users can see different charts about the details of their QSOs.

MONETŲ BAZĖS PORTFELIS

Lately I've taken an interest in home automation. A friend mentioned Home Assistant to me and after playing with it for a bit I quickly became a big fan. I run Home Assistant on a headless Raspberry Pi which has helped me to become familiar with Linux. One thing led to another, and now I have an excessive number of Docker containers of different home automation software running on my Pi.

Node-RED is one of my favorites. Using Node-RED, FIND3, and Tasker (on my phone), I created a convoluted parking location tracker. In my area there are parking restrictions between certain hours on certain days of the week. These times vary depending on what side of the street you are parked on. When my phone disconnects from my car's Bluetooth it gathers GPS and WiFi signal strength data and sends it to Node-RED. Node-RED then messages me on Telegram asking what side of the street I'm parked on. It then sends the street info along with the GPS and WiFi info to the FIND3 learning API. Node-RED monitors the time and FIND3's location prediction and notifies me if I need to move my car soon.

I intend to keep the learning step in place until FIND3 becomes reasonbly accurate, but so far it just isn't there. I likely need many more data points for each side of the street before it improves. Another issue could be that the WiFi fingerprints aren't unique enough since the houses are close together.

KIEK BITKOINŲ SUKURIAMA KIEKVIENĄ DIENĄ

The app interfaces with a FIND3 server to determine what room you are in and will notify you if there are tasks to be performed in that room. For example, if you are in the kitchen the app might present a notification saying "Don't forget to do the dishes!". The app has three components:

• DoWhere app: An app I am creating using React Native to communicate with a FIND server and DoWhere API, manage tasks, and notify when a task is available.
• DoWhere API: A simple CRUD API I created using NodeJS, Express, and MongoDB. The app will interface with this to manage user tasks.
• FIND3 server: Determines the location of a device in the house based on a fingerprint created by the WiFi and Bluetooth signal strength of nearby access points. A user can either host their own or use the public server. Created by schollz on GitHub.

So far the user can choose to enter the address of their own FIND3 server or use the public one. After that the app contacts the FIND3 server and retrieves a list of users, which is then displayed as a picklist. The app then queries the FIND3 server for a list of rooms and checks it against the DoWhere API to see if the user has any tasks in those rooms. Building the app is a relatively slow process since I am learning React Native as I go, but I am really enjoying it!

In the future I'd like to create other apps that interface with a FIND3 server to create a unique smarthome experience.