#dweet.io

BLE 以太網精簡網關是數據採集器通過以太網傳輸把從 BLE（低功耗藍牙）所收集到的數據傳送到雲服務器。

系統配置

整個系統包含數據發送器，數據採集器和雲服務器。數據發送器測量心臟速率和發送到數據收集器。對於數據發送的軟件，我們使用 Nordic 提供的ble_app_hrs_s110 示例代碼。我們將使用虛擬數據為心臟速率和電池電量。

數據收集器收集由數據發送方發送來的數據，和所收集的數據發送到雲服務器。 （在這個帖子中，我們將使用 “dweet.io” 的服務）。對於數據採集器的軟件，我們結合了 Nordic 的 ble_app_hrs_c_s120 例程和 W5500 IO 庫。

The last big component I'm adding to Node-IOTDB is the concept of a "store", basically a place you want to send data. Example data stores are Dweet.io, Xively, Zatar and Data.Sparkfun.com / Phant.

Here's a complete example - track everything I know about:

var iotdb = require('iotdb') var iot = iotdb.iot() iot .store('dweet.io') .track( iot.connect() )

That's it - every single thing in my home network (as discovered by iot.connect() will be sent to dweet.io (by the track method).

For example, here's the temperature from one sensor in my house:

http://dweet.io/follow/urn:iotdb:device:3ce6a7f8f8a75088f30122863067aa64

{ "temperature": 65, "@context": "https://iotdb.org/dpjanes/models/smart-things-temperature", "@type": "smart-things-temperature", }

The @context and @type are JSON-LD markers that tell you how you - or especially your code - can interpret the word temperature. If you go to the @context you can see the exact definition of that value.

Article about Bug Labs / Freeboard / Dweet.io. Note re: Quinnell's last comment that change in IT often comes from the bottom, and it's easier to make a useful simple product more complicated than to make a complicated product simpler.

Yet, while web-enabled lights, door locks, thermostats, and the like are mildly useful devices, what consumers really want is automated functions like preparing the house to welcome them home. Similarly, companies want complete solutions that use the IoT, not just devices. It is the role of web services to provide that integrated behavior, and usually for a fee. Gartner expects that 80% of the IoT revenues will come not from devices, then, but from the services that those devices enable.