If you have an RTL-SDR compatible radio there’s an excellent chance you’ve heard of the rtl_433 project, which lets you receive and decode signals from an ever-expanding list of supported devices in the ISM radio bands. It’s an incredibly useful piece of software, but the fact that it requires an external software defined radio and a full-fledged computer to run dictated the sort of projects it could realistically be used for.
But thanks to the rtl_433_ESP Arduino library developed by [NorthernMan54], we’re now able to pack that functionality into a much smaller package. All you need is an ESP32 microcontroller and a CC1101 or SX127X transceiver module. If you’re looking for a turn-key hardware platform, the documentation notes the LILYGO LoRa32 V2 board includes the required hardware, plus adds a handy OLED display and microSD slot. It should be noted that the range of these radios don’t compare particularly well to a full-size RTL-SDR device, but that probably won’t come as much of a surprise. Continue reading “Arduino Library Brings Rtl_433 To The ESP32”→
When [Elixir of Progress] was looking at setting up environmental sensors around their home to keep track of temperature, humidity and such, the obvious ideas of using WiFi-connected sensors didn’t work due to lack of WiFi range. Although Zigbee (Z-wave) sensors have longer range than WiFi, they are decidedly more expensive, proprietary and require a special transceiver hub. That’s where 433 MHz sensors for weather stations come into the picture.
The idea is simple: virtually all of those sensors – many of them rated for outdoor use – use the unlicensed 433 MHz spectrum that can easily be captured using cheap RTL-SDR (software defined radio) USB dongles. With the data stream from these sensors captured, the open source rtl_433 project enables automatic decoding of these data streams for a wide range of supported sensors.
While Realtek RTL2832-based and other RTL-SDRs can be found for quite cheap, it should be noted that these can run quite hot. Rather than heatsinking the IC, for this project it was elected to only listen sporadically and allow the RTL-SDR receiver to cool down in between listening sessions.
Getting the data from there into Home Assistant, InfluxDB or similar is easy, as rtl_433 can output the decoded data directly to an Influx database, MQTT broker as well as other formats. In this case, the data was sent via MQTT with the Home Assistant instance configured to treat these MQTT topics as sensors. With each sensor’s location carefully registered, this allows for setting up a dense, very low-power network of 433 MHz sensors for monitoring and home automation purposes.
Before the Medtronic Bravo Reflux Capsule was attached to his lower esophagus, [James] got a good look at a demo unit of the pencil-width gadget. Despite the medical technician telling him the device used a “Bluetooth-like” communications protocol to transmit his esophageal pH to a wearable receiver, the big 433 emblazoned on the hardware made him think it was worth taking a closer look at the documentation. Sure enough, its entry in the FCC database not only confirmed the radio transmitted a 433.92 MHz OOK-PWM encoded signal, but it even broke down the contents of each packet. If only it was always that easy, right?
Of course he still had to put this information into practice, so the next step was to craft a configuration file for the popular rtl_433 program which split each packet into its principle parts. This part of the write-up is particularly interesting for those who might be looking to pull data in from their own 433 MHz sensors, medical or otherwise
Unfortunately, there was still one piece of the puzzle missing. [James] knew which field was the pH value from the FCC database, but the 16-bit integer he was receiving didn’t make any sense. After some more research into the hardware, which uncovered another attempt at decoding the transmissions from the early days of the RTL-SDR project, he realized what he was actually seeing was the combination of two 8-bit pH measurements that are sent out simultaneously.
We were pleasantly surprised to see how much public information [James] was able to find about the Medtronic Bravo Reflux Capsule, but in a perfect world, this would be the norm. You deserve to know everything there is to know about a piece of electronics that’s going to be placed inside your body, but so far, the movement towards open hardware medical devices has struggled to gain much traction.
We don’t know where [Scott M. Baker] calls home, but it must be a pretty humid place indeed. After all, he has invested quite a bit in fancy vacuum storage containers to keep his 3D-printer filament dry, with the result being this sensor-laden filament drying farm.
[Scott] wasn’t content to just use these PrintDry containers without knowing what’s going on inside. After a little cleaning and lube to get all the containers working, he set about building the sensors. He settled on a wireless system, with each container getting a BME280 temperature/humidity/pressure sensor and an SYN115 315-MHz ISM band transmitter module. These go with an ATtiny85 into a compact 3D-printed case holding a little silica desiccant. The transmitters are programmed to comply with ISM-band regulations – no need to run afoul of those rules – while the receiver is just an SDR dongle and a Raspberry Pi running rtl_433. The long-ish video below details design and construction.
The idea behind these vacuum containers would seem to be to pull out humid air and prevent it from coming back in. But as [Scott] quickly learned from his telemetry, following the instructions results in the equivalent atmospheric pressure of only about 2700′ (823 meters) elevation – not exactly a hard vacuum. But as [Scott] points out, it’s enough to get a nice, tight seal, and his numbers show a lowered and constant relative humidity over time.