Enabling the “Where and When” of IoT
For many designers of IoT devices that will be communicating over a range of about 100 meters, the options are many and somewhat confusing. There’s Bluetooth IEEE 802.15.4 (ZigBee, Thread, Wireless Hart and others), Z‑Wave, and of course Wi‑Fi, with all its various flavors.
Sorting through them becomes even more interesting as they each expand their capabilities with respect to range, mesh networking capability, native Internet Protocol (IP) support, data throughput and power consumption.
For example, the Bluetooth SIG plans in 2016 to extend Bluetooth’s official range by 4x, which would be from 10 to 40 m for a Class 2 radio. Of course, the SIG only defines the minimum range of 10 m: in reality, vendors’ implementations vary, and with a good radio and antenna design on a gateway’s receiver, the range of the current Bluetooth low energy could easily reach 100 m, with Classic Bluetooth reaching up to 1 km. The Bluetooth SIG also plans to add mesh functionality to Bluetooth low energy.
The Bluetooth SIG also plans to double the data rate for Bluetooth low energy, which would mean going from 1 Mbits/s to 2 Mbits/s gross rate, while also lowering its latency. For industrial applications, latencies in the range of 10 ms are needed if a system is to be able to react in a timely manner to an anomaly: fail‑safe capability is critical for industrial IoT systems and devices.
However, an area of focus is on location capability, along with other contextual data. Many Bluetooth radios already have a temperature sensor built into them, so that’s a good starting point. For location alerts, iBeacons, introduced by Apple in 2013, have become popular but are not terribly accurate, having difficulty resolving ranges of under 1 m (Figure 1.) The primary profile used here, the proximity profile (PXP), uses the received signal strength indicator (RSSI) to determine range, but given the vagaries of any given environment, in terms of interference and absorption, RSSI can be misleading, and only gets worse as distance increases.
Figure 1. Bluetooth iBeacons rely upon the relative strength of RF signals to determine position, so are not as accurate as time‑of‑flight (ToF) methods which are not as subject to signal absorption and RF propagation issues.
For truly accurate positioning, down to the centimeter, calculations based angle of arrival (AoA) and angle of departure (AoD), are all well studied and have been proven effective (Figure 2.)
Figure 2. To add the “where,” a GNSS‑enabled gateway can be augmented by short‑range wireless technologies employing angle‑of‑arrival, angle‑of‑departure, RF fingerprinting and time‑of‑flight analysis.
For example, ToF over Wi‑Fi, which measures how long it takes a packet to get from a transmitter to a receiver, has already been shown to be accurate to under 30 cm. For tracking assets such as blood, the combination of temperature and accurate location data can be critical.
Designers can combine this data with accurate time stamping from GPS‑enabled gateways that can provide high accuracy (Figure 3.) And those gateways don’t have to be expensive dedicated devices: a smartphone has the capability to provide that information, and connect the data to the cloud using any of its multiple wireless – or even wired – interfaces.
Figure 3. To get the “when,” GNSS‑based time stamping can be used to get accuracy in the nanosecond region. Other techniques include PTP, NTP and even time‑of‑flight.
Other positioning techniques include fingerprinting, which maps the RF paths from known Wi‑Fi access points or cellular towers to also get a good idea of a device’s position.
For applications such as vehicle‑to‑infrastructure (V2I), vehicle‑to‑vehicle (V2V) or vehicle‑to‑everything (V2X), it’s also important to seek the lowest communications latency, hence the move to radios based on IEEE 802.11p in the 5.9‑GHz band with a 10‑MHz channel with suitable protocols to ensure signal delays are kept in the sub‑50‑ms range.