The Fourth Industrial Revolution, also known as 4IR and Industry 4.0, improves manufacturing through the use of technology. The end-aims are to significantly improve productivity, reduce production delays and, for example, avoid penalties or future lost orders due to delayed work.
A key part of The Fourth Industrial Revolution is asset tracking that provides faster and more accurate stock control, item picking, job tracking, capacity measurement, demand analysis and product protection through sensing and automatic auditing.
It’s important that asset tracking is continuous because merely scanning things in/out using barcodes is open to human error and location is otherwise only as good as the last scan. Historical data is also important because it identifies blockages allowing processes to be refined.
When evaluating asset tracking systems consider:
Scalability and Performance – How many things do you need to track today and into the future?
Flexibility – Many of our customers initially buy an RTLS for one urgent purpose but later end up use the system system for additional needs.
Security – Where is your data stored and where does it go?
Look for a stand-alone solution rather than SAAS for greater performance, flexibility and longevity. While SAAS based systems can be a quick way into RTLS, they soon become limiting because you are sharing a platform with other customers. SAAS platforms usually don’t scale well technically and financially and don’t have efficient, direct access to the data for efficient ad-hoc reporting. They also pose potential security and reliability risks as you don’t own your data. The ultimate limitation comes when the SAAS provider, usually a startup, eventually increases costs, get’s bought out by its largest customer or goes out of business.
Connected factory implementations require a large number of connected assets for condition-based monitoring, asset tracking, inventory (stock) management or for building automation. Bluetooth is a secure, low cost, low power and reliable solution suitable for use in connected factories. In this post, we examine the reasoning behind some out-of-date thinking on industrial wireless, uncover the real problems in factories and provide some explanations how Bluetooth overcomes these challenges.
Operations teams are usually very sceptical about industrial wireless. They have usually tried proprietary industry solutions using wireless with mixed results. They might have experienced how connections, such as WiFi, can become unreliable in the more electrically noisy areas of factories. The usual approach is to use cable. However, this can become expensive and time consuming. Using cable isn’t possible when assets are moving and becomes impractical when the number of connected items becomes large as in the case of connected factories. As we shall explain, Bluetooth is intrinsically more reliable than WiFi even through they share the same 2.4GHz frequency band.
There’s usually lots of electrical noise in an industrial environment that tends to be one of two types:
Electromagnetic radiation emitted by equipment. This typically includes engines, charging devices, frequency converters, power converters and welding. It also includes transmissions from other radio equipment such as DECT phones and mobile telephones.
Multipath propagation which is reflection of radio signals off, usually metallic, surfaces and received again slightly later.
It’s important to understand how Bluetooth and other competing technologies react to these types of interference. There’s a useful study (pdf) by Linköping University, Swedish Defence Research Agency (FOI) and the University of Gävle on noise industrial environments.
Noise in industrial environments tends to follow the following spectral pattern:
Electrical noise spectrum
There’s usually lots of electrical noise up to about 500MHz. This means wireless communication using lower frequencies, such as two way radio, exhibits a lot of noise. Pertinently, several wireless solutions for industrial applications use frequencies in the 30–80 MHz and 400–450 MHz bands. Bluetooth’s and WiFi’s 2.4GHz frequency is well above 500MHz so exhibits better reliability than some industrial wireless solutions. Incidentally, in the above charts, the peaks around 900 MHz and 1800 MHz mobile phone signals and 1880–1890 MHz come from DECT phones.
The magnitude of multipath propoagation depends on the environment. It’s greatest in buildings having highly reflective, usually metallic, floors, walls and roofs. If you imagine a radio signal wave being received and then received again nanoseconds later, you can imagine how both the amplitude (peaks) and the phase of the received signal becomes distorted over time. Bluetooth uses Adaptive Frequency Hopping (AFH) which means that packets transferred consecutively in time do not use the same frequency. Thus each packet acts like a single narrowband transmission and there’s less affect of one packet on the next one. However, what is more affected is amplitude which manifests itself as the received overall signal strength (RSSI). RSSI is often used by Bluetooth applications to infer distance from sender to receiver. We will mention mitigations for varying RSSI later.
It’s important to consider what happens when there is electrical noise. It turns out that technologies invented to ensure reliable transmission behave much less well in noisy situations. One such technique is carrier sense multiple access (CSMA), used by WLAN (WiFi), that listens to the channel before transmitting and waits until a free channel is observed. CSMA and automatic auto repeat (ARQ) also have re-transmission mechanisms. The retrying can also incur significant extra traffic that can overwhelm the communication in noisy environment. Bluetooth doesn’t use such schemes.
The previously mentioned research classifies different wireless technologies according to the delay when used in noisy environments:
Bluetooth (and WISA) is a good choice for noisier environments. It’s particularly suited for applications with lower data rates and sending at periodic intervals.
A final consideration is interference between Bluetooth and other technologies, such as WiFi, that use similar 2.4GHz frequencies. As mentioned in a previous post, there’s negligible overlap between Bluetooth and WiFi channel frequencies.
In summary, Bluetooth is more suited to electrically noisy environments and also offers low cost, low power and secure wireless communication.
These conclusions correlate well with our own empirical observations. We have found that Bluetooth advertising is still received in environments we have measured, using a RF spectrum analyser, to be electrically noisy around 2.4GHz . We believe this is because Bluetooth advertising hops across three frequencies such that there’s less likelihood of noise on all three. Advertising is also very short, typically taking 1 or 2 ms, making the coincidence of the noise and the advertising less likely than would be the case of a longer transmission.
It has been our experience that solutions using Bluetooth advertising are more reliable than those using Bluetooth (GATT) connections, especially in noisy environments when it’s difficult to maintain the chatty protocol of a connection over a long time period. In noisy situations, advertising is usually seen on a future transmit/scan if the first advertising is lost. By coincidence or design, Bluetooth Mesh is built on communication via advertising rather than connection and for this reason is also reliable on the factory floor.
However, using Bluetooth isn’t a silver bullet. There are situations where factories, or more usually parts of factories, have reflective surfaces or unusual radio frequency (RF) characteristics stretching into unforeseen frequencies. Poorer performing WiFi also needs to be considered in context of choosing between Ethernet and WiFi gateways and Bluetooth mesh.
It’s important to do a site survey including RF spectral analysis. This will uncover nuances of particular critical locations or coverage that can drive subsequent hardware planning. It can also feed into requirements for software processing, for example particular settings for processing within a real time locating system (RTLS) to cater for more varying RSSI.
Customers often ask us the accuracy when locating beacons. In order to get the answer, its necessary to understand different ways of locating and the tradeoffs that are needed to get the different levels of accuracy.
There are two types of locating, received signal strength (RSSI) based and angle of arrival direction finding (AoA).
Locating using RSSI
There are two main scenarios. The first is a where the detector, usually a phone or gateway, is at a known location and the beacon moves. The second is where the beacons are fixed and the detector moves. Either way, the detector receives a unique beacon id and the receiving electronic circuitry provides the strength of the received signal.
The value of the RSSI can be used to infer the distance from the detector to the beacon. The main problem with RSSI is that it varies too much, over time, to be used to accurately calculate distance. The direction also isn’t known when there’s only one beacon and one detector. The varying RSSI, even when nothing is moving, is caused by the Bluetooth radio signals that are reflected, deflected by physical obstacles and interfered with by other devices using similar radio frequencies. Physical factors such as the room, the beacon not uniformly emitting across a range of 360 degrees, walls, other items or even people can affect the received signal strength. How the user holds a detecting phone can affect the effectiveness of the antenna which in turn affects the signal strength.
The varying RSSI can be smoothed by averaging or signal processing, such as Kalman filtering, to process multiple RSSI values over time. The direction not being known can be solved by using trilateration where three gateways (or beacons depending on the above mentioned scenario) are used to determine the distance from three directions and hence determine the 2D location.
Trilateration
The aforementioned physical factors that affect RSSI can be reduced by measuring the actual RSSI at specific locations and hence calibrating the system.
The change of RSSI with distance is greater when the beacon is near the detector. At the outer reaches of the beacon signal, the RSSI varies very little with distance and it’s difficult to know whether the variance is due to a change of distance or radio noise. Hence for systems that use signal processing, trilateration and calibration tend to achieve accuracies of about 1.5m within a shorter range confined space and 5m at the longer distances.
However, such systems have problems. The multiple RSSI values needed for averaging or signal processing mean that you either have to wait a while to get a location fix or have the beacons transmit more often (with a shorter period) that flattens their batteries much sooner. Trilateration requires at least three devices per zone so can be costly and require significant time to setup and maintain. Using calibration is like tuning a performance car. It works well until something small changes and it needs re-tuning. If someone adds a room partition, desk or even something as simple as lots of people in the room, the calibration values become invaid. Re-calibration takes human effort and, pertinently, it’s not always easy to know when it needs re-tuning.
An alternative to trilateration is zoning. This involves putting a detector (or beacon depending on the above mentioned scenario) in each room or zone. The system works out the nearest detector or beacon and can work on just one RSSI value to get a fix quickly. The nearest zone is often all that’s required of most implementations. With zoning, if you need more accuracy in a particular zone you add more detectors in the area to get up to the 1.5m accuracy of other methods. This will obviously be impractical if you need 1.5m accuracy everywhere over a large area.
An alternative to trilateration and zoning is more expensive Bluetooth hardware and more complex software that makes use of Angle of Arrival (AoA). Locator hardware with multiple antennas uses Bluetooth Direction Finding to find assets to better than 1m accuracy. Location engine software uses the difference in the time of receiving the signals at multiple antennas to calculate the position. Multiple locators can also be used to cover larger areas and/or improve the accuracy using triangulation.
Unlike RSSI systems where any beacons can be used, locators tend to be tied to using the same manufacturers’ beacons. The complex hardware and software has less throughput and supports fewer beacons. The computing hardware needs to be more powerful. Systems need careful, accurate site measurements to achieve good accuracy.
Summary
Choosing a solution just because it is more accurate, rather than needed, will cost significantly more not just in hardware but in software cost, setup effort and maintenance. Work out what accuracy you need and then seek out an appropriate solution.
