"ZigBee" entries

How to identify a scalable IoT network topology

Range, power consumption, scalability, and bandwidth dominate technology decisions.

HVAC Air Group in an airlift. Source: Hvac en kabelgoot

HVAC Air Group in an airlift. Source: Hvac en kabelgoot

Editor’s note: this article is part of a series exploring the role of networking in the Internet of Things.

Three types of networking topologies are utilized in the Internet-of-Things: point-to-point, star, and mesh networking. To provide a way to explore the attributes and capabilities of each of these topologies, we defined a hypothetical (but realistic) application in the building monitoring and energy management space and methodically defined its networking requirements.

Let’s pull it all together to make a network selection for our building monitoring application. As described previously, the application will monitor, analyze, and optimize energy usage throughout the user’s properties. To accomplish this, monitoring and control points need to be deployed throughout each building, including occupancy and temperature sensors. Sensor data will be aggregated back to a central building automation panel located in each building. A continuous collection of data will provide a higher resolution of temperature and occupancy information, thus rendering better insight into HVAC performance and building utilization patterns. Comparison of energy utilization throughout the portfolio of properties allows lower performing buildings to be flagged.
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Four short links: 1 August 2014

Four short links: 1 August 2014

Data Storytelling Tools, Massive Dataset Mining, Failed Crowdsourcing, and IoT Networking

  1. MisoDataset, a JavaScript client-side data management and transformation library, Storyboard, a state and flow-control management library & d3.chart, a framework for creating reusable charts with d3.js. Open source designed to expedite the creation of high-quality interactive storytelling and data visualisation content.
  2. Mining of Massive Datasets (PDF) — book by Stanford profs, focuses on data mining of very large amounts of data, that is, data so large it does not fit in main memory. Because of the emphasis on size, many of our examples are about the Web or data derived from the Web. Further, the book takes an algorithmic point of view: data mining is about applying algorithms to data, rather than using data to “train” a machine-learning engine of some sort.
  3. Lessons from Iceland’s Failed Crowdsourced Constitution (Slate) — Though the crowdsourcing moment could have led to a virtuous deliberative feedback loop between the crowd and the Constitutional Council, the latter did not seem to have the time, tools, or training necessary to process carefully the crowd’s input, explain its use of it, let alone return consistent feedback on it to the public.
  4. Thread a ZigBee Killer?Thread is Nest’s home automation networking stack, which can use the same hardware components as ZigBee, but which is not compatible, also not open source. The Novell NetWare of Things. Nick Hunn makes argument that Google (via Nest) are taking aim at ZigBee: it’s Google and Nest saying “ZigBee doesn’t work”.
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Mesh networking extends IoT reach

A suitable network topology for building automation.

XBee_Series_2_with_Whip_AntennaEditor’s note: this article is part of a series exploring the role of networking in the Internet of Things.

Today we are going to consider the attributes of wireless mesh networking, particularly in the context of our building monitoring and energy application.

A host of new mesh networking technologies came upon the scene in the mid-2000s through start-up ventures such as Millennial Net, Ember, Dust Networks, and others. The mesh network topology is ideally suited to provide broad area coverage for low-power, low-data rate applications found in application areas like industrial automation, home and commercial building automation, medical monitoring, and agriculture.

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