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I ordered a bunch of ESP8266 modules in November and I have been developing applications since then with the available environments: 1 - Arduino IDE 2 - MicroPython 3 - Native SDK Arduino IDE is great because it allowed me to re-use the code I wrote to access Azure through REST for my Azure Watering System. Having both WiFi and a low power MCU I decided to build a Wireless station to monitor Humidity and Temperature and report to Azure. Several SSIDs may be included in the program, therefore this monitoring device may be used inside and in the surroundings of my home - connected through home WiFi, or anywhere if I connect through my 3G+ phone. The actual challenge for a Wireless station is to be REALLY wireless, this means running on battery. I used a 400MAh 1S LiPo I had in stock to see how long it would run between recharge. The actual setup is as follows: This includes more than the ESP8266 and DHT11 shield (in the back) and Battery (in front), 1 - The display and resistors are used to measu ...
Now my Azure watering system has been running for a few weeks and I can use collected data to undestand how it behaves. The data on Azure lead to the following graphs: The big watering bars correspond to manual watering, from this graph I understand several key points: 1 - Humidity level should be maintained between 50 and 300 2 - Cooler temperatures in November have minimized evaporation ...or plants consumption 3 - The humidity variation during a day may be important compared to the interval given before 4 - All humidity sensors seem to follow an identical pattern, but my pots are not identical!! To know more about humidity Sensors, i will modify the configuration, two sensors will be installed in test tubes, one completely immerged and the other one half immerged . With this 100% stable configuration and Azure data recording, I expect a clarification on humidity measurement.
My Azure watering system did work by itself during my vacation, and thanks to Azure recorded data I know a bit more about humidity and watering. The data history shows an unexpected behavior: Water has been pumped everyday in the pots without raising the level of humidity, the big bars on september 10th (300) correspond to manual watering. I also noticed that water was spilled under the pots, meaning that it was going through the soil - totally inefficient!! Also the correaltion of Azure data with real world showed that a humidity level of 200 was perfectly suitable for my trees. Now I'm ready to modify the program and watering plan: 1 - I must be able to control the levels and timings remotely, I added a "parameter" table in Azure 2 - I must make four measures per day because humidity values shown are unstable
My watering system monitored withAzure is now fully operational for three plants. The connected computer is an Educake from ICOP, it measures three sensors and is able to pump water individually in each pot. The system is connected to a timer socket progammed to wake up once a day. The information reported to Azure by the Educake contains humidity and watering time for each pot. This configuration has been running for a week and Azure data allows me to calibrate the watering parameters. Unplanted sensor (dry) gives a 1024 value, and fully dipped sensor gives a 400 value. As I'm checking humidity, I decide to reverse the scale : 600 = watered - 0 = dry, one week of recording shows the following graph: Now Let's go to vacation!...
Before my summer vacations, I decided to build a watering system for my decorative trees. The soil moisture is measured with a cheap IoT sensor and the water supply uses 12V airpumps pushing air in water bottles (this makes a safe separation between electric and water circuits), the electronic schema is as follows: The 86Duino Educake computer monitors the humidity level once a day and will pump water if the level is too low, it sends data to Azure therefore I'll be able to see how things are going on...
Following a cat's activity is not an easy task, Azure Mobile Services makes it possible with the help of a dedicated intelligent IoT system and REST appications.
In my previous blog Windows 10 (including IoT) USB HID device identification was covered in detail. This included an app that takes the relevant IDs for an HID device and checks whether it is present on the system. Two of the IDs could be looked up via a menu as they come an HID Usage table. The menu data was loaded from a JSON (text) file and translated using Linq to a list that is the Xaml data source binding for the menu. This blog demonstrates the mechanism for loading JSON data from a text file into an Xaml ComboBox.
Human Interface Devices (HID) are supported in the “headful/headed” (viz. headless) version of Windows 10 IoT. Anything that takes users input for an app is an HID device, and can include devices such as screens that provide feedback to the user. Traditional HID devices are the mouse and keyboard, whereas gaming devices such as joystick, XBox controller and steering wheel are also HID devices. A barcode scanner or credit scanner are also be HID devices, A system with just a few push buttons to control it has those pushbuttons as a trivial HID. Technically the HID protocol was developed as a protocol for the USB-HID class such that devices that conform to that class do not need a specific driver.
Whilst the Raspberry Pi 2 has extensibility through GPIO, I2C, SPI and Single wire, the main interface for adding off-the-shelf peripherals is via USB. Unlike the desktop, there is though only a limited set of USB peripherals that can be used on the RPI2 running Windows 10 IoT in the first release. This series of articles looks at what is available and what the overarching issues are. The first Article is “Connected Devices”
Peripheral devices can be connected to the Raspberry PI 2 via the four USB host ports. The connected devices can be examined in a number of ways. This blog examines these methods.