You can probably agree that range is one of the most important factors when determining what wireless communication system to use for industrial asset tracking and monitoring. Many companies choose Bluetooth Low Energy (LE) due to its reduced power consumption and extended battery life, in turn resulting in lower infrastructure costs. The question is, how do you determine range in varying industrial environments? Let’s explore how to calculate and improve range of Bluetooth LE systems.

How to Determine Range

What is range? Range is how far away a transmitter can be from a receiver while still being able to accurately read information it’s sent. In order to determine this, there are some factors that must be identified. Before identifying the different factors that affect Bluetooth Low Energy range, let’s clarify some details about what it means for a transmitter to “send information” and a receiver to “read” it.

First, a transmitter sends small bits of information through radio signals. In the case of Bluetooth LE, the radio signals are sent in the frequency of 2.4 GHz using adaptive frequency hopping technology to avoid interference by other protocols, such as Wi-Fi and Zigbee, that travel through the same bandwidth. These signals are also sent with a specific power level measured in decibel milliwatts (dBm).

The receiver then “reads” the signal and interprets the data being sent. The ability to “read” the signal is determined by the receiver’s sensitivity which is the measure of the minimum signal strength a receiver can detect and interpret. However, the effort to “read” the transmission can be improved or diminished through a variety of factors as the signal travels to the receiver. These factors include antenna gain, path loss, propagation loss, structural attenuation, and other interferences.

Ultimately, you must have a receiver sensitive enough and a transmitter powerful enough for the receiver to hear the transmission through power losses. The link budget is an effective way to calculate the total gains and losses of the transmission signal as it travels from the transmitter to the receiver.

Factors Affecting Strength of Signal Received:

  • Antenna gain – Converting electrical energy to electromagnetic energy or vice-versa and focusing the direction of the energy to impact effectiveness of transmitted signal and received signal. Antenna location, size, and design can vary and impact its effectiveness.
  • Path loss – Reduction in signal strength that occurs as a radio wave propagates through the air. 
  • Propagation loss - The spreading out of RF energy as the signal dissipates typically due to the RF wave interfering with itself as it bounces off the ground. 
  • Attenuation loss - Losses associated with propagation through material other than air like humidity, precipitation, walls, glass, etc.

Check out our Range Calculator to find a range estimate for your network.

Improving Bluetooth Low Energy Range with Mesh Networks

Though the range of communication between two Bluetooth LE devices may be somewhat limited based on environmental conditions, there is a way to make this into a scalable solution. That’s by using either a Full Mesh Network or Partial Mesh Network.

full mesh network ble range

Full Mesh Network

In a full-mesh network, a large number of Bluetooth devices are connected over a wide area. Those devices communicate either directly with each other or across intermediate “nodes” (other Bluetooth devices in the mesh network). As long as each node is close enough to communicate with at least two others, this mesh network can operate.

Some benefits of a full-mesh network are its Self-healing or Shortest Path Bridging ability which automatically selects the best route to communicate information even when certain nodes lose connection. On the other hand, if you want to generate collective action from your Bluetooth devices, “broadcasting” a message to all the nodes in the mesh network will give you your desired result. Since nodes can be added and taken away without previous set-up, mesh networks are also easily scalable. There is a great deal of redundancy in a full-mesh network, however, which means higher-power consumption for the Bluetooth tags and higher costs for you.

Partial-Mesh Network

Another way of connecting Bluetooth devices is with a partial-mesh network. In this scenario, not all devices are connected to each other directly. Each device is connected to at least two other nodes, but only a portion of them might be organized in full-mesh topology, if at all. As a result of this organization, redundancy is reduced, and costs can be significantly cut down.

Making Use of XLE for Asset Tracking

Though these mesh networks come with their own advantages, there are many complications when it comes to implementing them into a comprehensive asset tracking and monitoring system. One can admit that it is not easy to obtain both accuracy and affordability with this type of infrastructure. However, AirFinder OnSite achieves both with its industry-leading XLE™ (Xtreme Low Energy) technology and reliable LPWAN Symphony Link.

XLE is a newer version of Bluetooth LE that Link Labs patented at the end of 2020. XLE technology identifies asset location within one meter of accuracy through phase-ranging, and with proprietary firmware, the battery of the asset tag can last up to 7 years.  XLE extends battery life by more than 400% through a more intelligent use of energy conservation.

In summary, sending data via Link Labs’ reliable LPWAN, that covers as much as 1 million square feet, dramatically reduces costs, and the range of the XLE network is exponentially increased. In addition to phase-ranging technology, improved battery life, and reduced latency of AirFinder’s XLE tags, the system runs effectively through a partial mesh network without compromising range, security, accuracy, or affordability. To see AirFinder OnSite XLE in action, request a demo today.

bluetooth low energy for asset management

Philip Bender

Written by Philip Bender

Philip Bender is a data analytics leader with a specialty in data integration, business intelligence, and applied statistics. He has over 15+ years of experience with proven success in designing, building, and delivering syndicated and customized data analytics solutions to meet and exceed client needs within multiple industries. He has expertise in advising clients on complex and critical business issues such as understanding consumers, prioritizing market opportunities, and acquiring and retaining customers. Prior to Philip’s current role at Link Labs, he worked in various fields under roles such as Senior Analytics Consultant and Director of Analytics, Applied Statistics, and Product Innovation. Philip has an educational background in political science and mathematics, where he fulfilled his studies at the University of Notre Dame.

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