The Internet of Things (IoT) revolution has provided the industrial businesses the ability to know how things are working — be it machines, inputs, or processes. With IoT devices, using sensors and controllers that tell us its current status, we can monitor a machine and know how it is behaving. Information such as temperature, vibration and item count can be collected and monitored for analysis.
For static items such as machines and processes that do not change and always stay in the same place, this is enough. But there are other types of processes and objects about which we need to know not only operating data, but location. In response to this need, new technologies are being applied to determine the placement of these things indoors.
When we talk about positioning, the most common is to think of global positioning systems, such as GPS or GLONASS, which operate through satellite signals. Although they are systems with good accuracy and reliability and are already consolidated in the market, they present problems when used indoors — in a factory, for example —, where the signals are weakened due to walls and metal structures.
This weakening of radio signals in environments with walls and metal structures decreases the effectiveness of systems such as GPS, when applied to factories. Therefore, these systems are best for external use, such as in agribusiness or in the transport sector.
Indoors, systems that use radio to calculate the position of objects require beacons — transceivers in fixed and known positions — scattered throughout the space. Since the use of Wi-Fi has already become common in industrial environments, it is also the first option for determining the position of objects.
Wi-Fi routers that are already installed and IoT devices can use Received Signal Strength Indicators (RSSI) from multiple routers to determine their position. Systems such as Bluetooth and Zigbee can also use RSSI to locate IoT devices that already have these technologies installed.
The RSSI solution is relatively simple to implement, as it is a signal available on all radio modules in IoT devices. Since the signal level received by the device varies with the distance of the beacons according to the Friis equation, it is possible to determine the distances and, by triangulation, calculate the position of each device.
Due to multi-path problems — signals reflected in obstacles that are also received by antenna — it becomes necessary to use correction algorithms to mitigate the effects of these interferences and improve the accuracy of the positioning calculation.
Newer location solutions use Time of Flight (ToF) or Time Difference of Arrival (TDoF) methods. In both cases, the distance between the beacon and the device is calculated based on the time the radio signal takes to get from one point to another. In the case of ToF, the calculation measures the time the signal takes to go from the device to the beacon and back.
TDoF, in turn, is based on data packets. Since each beacon is in a different location, messages arrive at different time intervals. The time difference between the arrivals of the data packages is used to calculate the position of the device that sent them.
IoT devices can also receive location systems that do not use radio. The miniaturization of accelerometers and gyroscopes made with Micro-Electro-Mechanical Systems (MEMS), for example, made it possible to create inertial location units small enough to be used in these situations.
In this type of system, an initial position is given and the device calculates the others from its displacement. Another use of MEMS in positioning is the use of magnetic field sensors that detect variations in the Earth’s magnetic field from metal structures in a factory, for example.
Benefits and uses
Knowing the position, even if approximate, of something within a factory can save time and improve material flow in the factory. Unnecessary offsets to locate a particular item are eliminated, as the item’s location will be know in advance.
Maintenance technicians do not have to look for a cart or toolbox around the factory if they are IoT devices that have location systems. The technicians can consult a system or app that will tell them where the tools are and if they are in use at the moment.
The same cart or toolbox can also provide a log of their position. Analysis of this log can tell a human operator how many tools are used and for how long. The maintenance time can also be extracted by the time the toolbox or cart was stationary next to a piece of equipment.
In warehouses and industrial stocks, smart pallets can correctly indicate where they are, optimizing the work of pallet and forklift operators. The path traveled by the pallet at the factory premises is also recorded. Analyzing this information can lead to better routes and saving resources such as energy and movement.
The use of IoT devices with location systems increases the range of possibilities for improvements in industrial processes. Stocks, tools and other equipment come to inform and know not only how they are, but where they are. Item placement errors, out-of-place tools, loss of supplies and stock, and other issues are detected faster and operators save the time they would spend searching for items.
As global positioning systems (such as GPS or GLONASS) do not meet indoors needs, new technologies — smaller, with lower power consumption and greater accuracy — create new monitoring possibilities. The cost of these solutions enables the position monitoring of increasingly smaller items in storage or production areas.
Knowing where things are inside a factory creates new possibilities for resource analysis, improvement in the distribution routes of supplies for production and shipment stock control.