As the market for the Internet of Things starts to take shape, the role of wireless sensor networks in enabling a range of new applications, has started to take centre stage, with demand growing for extremely low power solutions.
While sensor-based networks for monitoring and control are not new concepts, demand for wireless implementations – previously limited to just a few niche markets – is set to grow as companies look to bene8t from the combination of installation simplicity and low-cost.
Wireless systems need to consume as little power as possible and next generation networks are being developed where batteries require little maintenance over the application’s life time. As an alternative, there is also a focus on energy harvesting to provide the necessary power, removing the need for batteries completely.
Energy harvesting is becoming more attractive because it doesn’t require continual recharging and does away with the need for communication or power wires. The challenge with its deployment comes when it needs to be located in more challenging environments and especially when power needs to be stored. If you have to incorporate temporary storage capabilities in a design, then the application will, as a necessity, become far more complicated – cost, as a result, then becomes a more important issue, especially if you are distributing hundreds or thousands of sensors.
Applications have different power requirements. A door lock, for example, may only have to report back every hour or when something happens. As a result the power requirements will be low. By comparison, some wearable devices, such as the Apple Watch, consume far too much power to deploy a harvesting solution. The challenge is being able to develop an MCU that is capable of driving an application but which comes with very low power consumption. When powering sensors is that energy harvesting may only be able to supply as little as 10μA ontinuously, especially if the energy source is a small solar panel.
By contrast, a microcontroller executing code will have power requirements hundreds or thousands times greater. As a result, application designs will need to be able to fully leverage various sleep modes and should be designed with a view to putting the application into sleep mode as much as is possible.
Most applications will come with a variety of preset operating modes, so the embedded microcontroller can, for example, be put into a ‘sleep’ or enter an extreme, low-power ‘standby’ mode in between different data samples. If the microcontroller collects sufficient data, it can then switch to a ‘fully on’ mode, where it is awake and running at maximum operating speed. This will require the microcontroller to receive some kind of wake-up event, which could be triggered by an external event or by internal processor activity.
From an ‘always on’ mode to a ‘sleep’ or ‘standby’ mode, where memory stays powered, or a ‘deep sleep’ mode, where the memory is powered down for maximum power savings, the choice of a microcontroller’s power modes can have a significant impact on the overall power requirements of an application.
The problem with energy harvesting solutions is the energy output might be too low to power up the MCU. Starting an MCU will require a lot of current; more than the energy harvesting component can provide. As a result, you need to deploy a mechanism whereby the MCU will only start-up when sufficient energy has been stored, usually a capacitor to store the energy and a comparator capable of detecting the amount of power available.
Once the application has powered up, it can then return to a more suitable power mode. It means the application has greater stability.
Accurate timing is needed to ensure the wireless sensor transmits information during a predefined assigned time slot, which will enable multiple wireless sensor nodes to work together.
The overall power budget of the wireless system, the transmit power consumption, the receiver power consumption, the standby power consumption, and the start-up time are all important considerations and will determine how much current the unit will consume when transmitting and receiving data.
To minimise the overall power consumption, it is not enough to simply select the lowest-power mode on the microcontroller as the amount of work needed to complete each of the tasks will need to be taken into account and as the Internet of Things develops and the amount of data collated rises, how and when that data is processed will become more important. At the moment, batteries remain the dominant way in which power is stored and delivered. While there has been a lot of discussion around energy harvesting, it really hasn’t taken off.
When you develop a network, there will be a power budget for computation and for communication. Hopping from one node to another to get that data to a point where it can be processed can be described, in effect, as an energy tax that you are taking from that packet or payload. Minimising those hops could be one trade-off leading to more localised processing should those tasks be more power intensive.
In many low-power saving mode systems, the application’s battery life will often be affected by the current consumption of other components in the PCB and this needs to be considered. components in the PCB and this needs to be considered. Designers will also need to determine which other circuits need to be powered in the low-power state of the application. Power requirements will have an impact on the roll out of the Internet of Things, but everything will depend on the application.
Cost and power among the challenges to rolling out of IoT applications, but note that, further down the road, security is another consideration. Consumers will start to worry when they begin to realise the devices they are using are less secure than they thought. When you connect to a network, there are some
expensive operations that need to be carried out and that will have an impact. Any security features will
need to be low power.