Feature: Sensors
Te definition of “remote I/O” is
very broad. For the purposes of this article we will apply it to any device that interfaces to sensors and digitises the resulting measurements before onward transmission. Tis means we encompass traditional remote telemetry units (RTUs) and remote I/O devices using protocols such as Modbus, but also USB devices aimed at lab measurements and fieldbus- based data-acquisition nodes, as well as more modern incarnations, such as IoT edge and gateway devices. Te use of any such device starts to introduce compromises that must be considered: • Digitising data implicitly places a constraint on the precision that can be recovered. Does the remote I/O device convert the data with enough resolution (i.e. number of bits) to be able to extract the nuances in the measurement required by any upstream analytics system?
• Is the quality of the measurement (accuracy, repeatability, noise immunity etc.) sufficiently good?
• Transmitting data either serially or via a network takes a finite amount of time, determined by the volume of transmitted data, protocol overheads to encapsulate it, the speed of the communications links, and the number of devices sharing the connection. Can data be recovered fast and frequently enough to provide the necessary insights and avoid any risk of missing measurement spikes between samples?
• Transmitted data oſten suffers from delays, duplication or loss, so how significant will any of these events be to the process being analysed or controlled?
Wireless system considerations Tere are many factors to consider when choosing a wireless system, including: • Powering the remote devices: Simple devices can operate from internal batteries for a certain period, but many still need more power, which means cables and costs.
• Interference immunity: How secure are the transmissions from eavesdropping or malicious actors blocking signals or imposter devices providing false information?
• Licencing: Do the radios operate in controlled, licenced airspace or at licence-free frequencies? If the latter, how can transmission be guaranteed against accidental disruption by other systems operating on the same frequencies?
• Costs of communications: Te costs of wired systems are normally limited to the capital cost (Capex) of purchasing and installing the equipment, but many radio-based systems involve ongoing operational expense (Opex), for example for cellular service provision.
• Reliability: Can it be improved by adopting systems with radio diversity with the chosen technology (i.e. automatic routing of signals via multiple path options, for example as found in mesh systems)?
• Working range: Teoretical ‘line of sight’ maximum distances can be significantly longer than actual distances, especially if transmitters are located in and around buildings, valleys or underground. Similarly, environments with many large moving metal objects, say forkliſt trucks, and/or water-filled objects, including people, can cause difficulties due to constantly- changing signal absorption, reflection and interference.
• Access and privacy: What public or shared infrastructure (e.g. cellular networks) will the data have to transit to reach its destination? How is access control performed and data privacy ensured?
Balancing act Recovering data from sensors in IoT systems is a balance of measurement performance, transmission speed, security, power, range and cost. It may not be a big surprise therefore to learn that there is no ‘magic bullet’ solution. Wired systems typically offer the best resilience and speed of acquisition, but are increasingly being matched by newer fieldbus-based systems. For lower-speed applications, wireless systems can offer a fast and cost-effective way to add further measurement points within an existing installation, provided they are able to operate effectively within their
Is a wired or wireless setup best for sensor deployment?
environment. Tey can be especially useful in overlay applications, where data is recovered from select points within existing installations and the existing systems are not easily interfaced to third- party systems. Challenges increase in remote data-
acquisition setups. Te best technology to adopt will depend not only on the factors discussed here, but on how many data points exist at each location. With a small number of sensors, it may be sensible to use native radio-based sensors such as those designed for networks like NB- IoT, LoRa or SigFox. If more sensors are present, then a more effective solution will be to have some form of input- aggregating edge device accepting inputs from all sensors but passing the resulting aggregated digitised values back through a single radio channel. Tis is especially true with smart edge, which can provide front-end filtering and transformation of the raw sensor data prior to transmission. Tis is not low-value repetitive data but significant events with implicitly higher value as actionable information. In many cases, the question should
not be presented as ‘either-or’. Oſten, the best results are achieved by mixing technologies, optimised for each measurement-point’s unique situation. Advantech offers a range of wired and wireless sensor interfaces as standalone devices and integrated within industrial computers and gateways. Covering the full range of available technologies including hardwired, fieldbus, serial, networked and radio via LTE, NB-IoT, mesh and LoRaWAN, there’s a solution for any situation.
www.electronicsworld.co.uk December/January 2021 49
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