How to make IoT edge devices power efficient?

Power efficiency is vital to the Internet of Things (IoT) success. The more efficient the device, the longer its functional lifespan and the better its user experience. Are you implementing an IoT solution in your organisation to make your IoT Edge devices more power efficient? This article highlights 15 critical factors you should consider.

Advances in low power management allow granular control over power consumption. Ultra-low power sleep modes such as standby, doze, sleep, and deep-sleep consume minimal current (ranging from microamps to nanoamps). Due to CMOS technology in IoT processors, power consumption increases linearly with clock frequency. The lowest power standby consumes approximately one-third of the current of the highest power option, but minimal processor state is saved. Some IoT applications may require the lowest power sleep modes, and the cache is preserved

Figure 1: Typical power-saving modes for IoT devices

Key takeaways

IoT devices rely on sleep modes and low-power management to save energy and extend battery life.
Battery-powered IoT devices must be energy efficient. You must adopt methods such as low-power components and optimised communication protocols for power savings.
Local data processing at the Edge effectively minimises power consumption.
Regular software updates are a must to improve power efficiency and solve power-related problems in IoT devices.

Context

The Internet of Things (IoT) is a massive network of connected physical devices seamlessly communicating through wireless and cellular connections. The network has many embedded sensors, software, and other technologies that help to connect and exchange data with other systems and devices over the Internet. The explosive growth of IoT applications and the adoption of energy-efficient methods has spurred the shift to Edge data processing.

Basics of operation

Figure-1 depicts a typical current profile mode of an IoT device. These devices are often idle, conserving energy and battery life. Modern MCUs have multiple low-power modes with different functions to reduce power consumption. Wake-up methods restore functionality in response to external events depending upon the sleep mode depth.

Tips and tricks

Power efficiency is crucial as IoT edge devices operate long and draw power from batteries. We will review various tips and tactics while powering up IoT devices.

Implement a sleep mode for IoT devices: Make smart use of sleep modes to decrease power consumption during inactive times. Set the device to low-power sleep mode when it is not actively processing data or doing operations to extend the battery life.
Energy harvesting techniques: Consider energy harvesting methods such as solar, kinetic, or thermal energy for charging or supplementing the device battery. This assures continuous functioning without the use of traditional batteries.
Avoid excessive push notifications: Limit the frequency and content of push alerts delivered to IoT devices. Allow such notifications only when necessary. These alerts may ‘wake up’ the device and needlessly drain the battery.
When and how the IoT device transfers information: Send information in batches or at predefined intervals rather than continuously to optimise data transfer. This reduces the problem of repeated connections and disconnections and saves power.
How features affect battery life: Conduct extensive power profiling to understand how your IoT device uses power to run its functions and components. Determine the energy-greedy components and prioritise energy-efficient alternatives or optimisations.
Select the most appropriate wireless protocol: Select a suitable wireless communication protocol for your IoT use case and power constraints. Various wireless communication technologies, including Wi-Fi®, Bluetooth® low energy, Thread and Zigbee®, and the emerging MATTER protocol enable device-to-device, device-to-cloud and device-to-mobile communication within home and building automation systems.
Use low power sensors: Select sensors that consume minimal power and use adaptive sampling techniques to alter sensor values based on environmental changes. This cuts down on unwanted sensor readings and saves energy.
Manage firmware and software updates: Ensure that firmware and software updates are energy-efficient and focus on improving power consumption where possible. Update devices on a regular basis with power-saving upgrades and bug fixes.
Low-power components: Use low-power microcontrollers, sensors, and communication modules. It is preferable to use the latest energy-efficient technologies and solutions if available. Consider components that have less standby and need minimum operating power.
Sleep mode and wake-up: Make efficient use of sleep modes to save power during inactive periods. Allow the device to wake up only when required by external events or timers. Reduce the amount of time spent in active mode.
Efficient communication protocols: Use energy-efficient communication protocols, such as MQTT-SN, CoAP, or LoRaWAN, depending on the specific use case and network requirements.
Duty cycling: Implement duty cycling techniques where the device periodically wakes up to perform tasks and then goes back to sleep. This reduces the overall power consumption, especially for devices with burst data processing needs.
Local data processing: Data preprocessing and filtering must be done at the Edge to decrease the quantity of data to be transmitted to the cloud. This greatly reduces power consumption during communication.
Power management ICs: Use only specialised power management ICs that are designed to maximise energy efficiency by regulating the power supply to various components.
Optimise display usage: Use low-power display technologies. If your device has a display, use low-power display technologies and turn off the display when not in use.

The firmware of the device must be optimised and updated on a regular basis to fix issues and increase power efficiency. Use dynamic voltage scaling techniques to alter the operating voltage of the components based upon their performance requirements. Doing this will help you to optimise power usage in various workload circumstances. Reduce your data size and transmission frequency. To minimise energy usage during communication, use data compression techniques and send only required information. Reduce the device's data processing workload by outsourcing certain functions to the cloud or edge servers. This can help to lower the device's processing needs and, as a result, its power consumption.