Testing the Nordic nPM1100 // Part 3: Comparing IoT Use Cases

Welcome to the last installment of our three-part series, which aims to take certain developer kit components — namely the nPM1100 evaluation kit — to manage power, an nRF development kit and some other miscellaneous components, and build a complete IoT device.

In part three, we will connect three different IoT use cases and see how they work in tandem with the nPM1100 evaluation kit. All of the below use cases will be utilizing the Seeed Studio XIAO board since it contains an nRF52840 chip and is very suitable for prototyping thanks to its compatibility with ArduinoIDE. We wanted to use the same board of our prototype ECG to truly carry out a comparison of consumption between projects with the same board but different software and components.

To see how efficient each use case is, we will measure them with Nordic's Power Profiler Kit. Learn more on how to read the current consumption of the nPM1100 evaluation kit with the Power Profiler Kit II (PPK2) in Nordic Semiconductor's official documentation.

If you're new to the series, be sure to also check out Part 1 - Hardware for the ECG where we looked at the dev kit integration, system's architecture, and component development and Part 2 - Software for the ECG where we wrote about the mobile app development along with some AI and cloud integration.

Use case #1: ECG

To use the device, an ECG cable connected to a patient's arms was connected to the ECG module, which has a jack input. Data is sent to the app using BLE at a frequency of 100Hz, enabling us to visualize a coherent graph. More documentation on this one in the first part of the series.

Communication with the ECG is done through the SPI protocol, unlike other more economical modules such as the AD8232 which are handled with analog readings and occupy an ADC. The power that we are supplying with the nPM1100 evaluation kit is 3v, which is the maximum voltage that the EK supplies.

We get the signals from our microcontroller through the nRF Cloud Gateway. We clean it a bit and then send it to our dashboard.

Power consumption

Connection of the POC to the PPK2 in ampere meter mode:

The current consumption that we have with the ECG device is 10mA with consumption peaks of 20mA since the nPM1100 evaluation kit can provide up to 150mA, so for low energy applications where we have a sensor like in this case, a low ECG consumption and a protocol like BLE, the nPM1100 evaluation kit is a perfect solution and, in my opinion, the most appropriate.

In comparison with our previous power management alternatives, I have seen (when measured with the PPK2) a reduction from 30% all the way to 300% depending on what you are measuring. But, perhaps, what is more important is that the nPM1100 stabilizes consumptions to a workable range which is something not every solution accomplishes.

Check out the PPK2 data here.

Use case #2: Illegal logging and fire detector

For this second use case, we decided to test the illegal logging and fire detector, which is a project that integrates AI and LoRaWAN to create a system that is capable of recognizing the sounds generated by falling trees, chainsaws and human voices in protected areas, thus warning that illegal logging may be occurring. Due to the current success of the Edge Impulse and Helium Network platforms, we found it very appropriate to observe the energy consumption of an application with this technology.

TVOC sensor

This sensor, in addition to measuring the eCO2 of the environment, provides us with the TVOC, a sensor that measures the amount of particles that can be harmful to humans if they are in the air. We can use it as a smoke detector. Since smoke usually contains many particles that are not "respirable," a high reading of particles can indicate a possible fire.

NOTE: The following demo was carried out in controlled situations. Starting a fire can be dangerous if proper care is not taken. We do not encourage these tests without supervision.

Edge Impulse

By using the Edge Impulse platform and our analog microphone, we were able to build an AI model that would allow us to differentiate between the human voice, a chainsaw, and ambient sound.

See the original published model and the inference model for the XIAO if you want to load it directly through ArduinoIDE.

The microphone is connected to the A1 input on our board for easy connection via a grove cable.

NOTE: It is highly recommended that instead of using an analog microphone like this, you use a PDM microphone since it is much more sensitive, allowing it to obtain data with much higher quality and much lower energy consumption.

Helium

For this device to communicate with the world, we will use LoRaWAN, with the extension of the module used on the Helium Network.

The LoRa E5 Grove module was used to easily connect with our XIAO board.

Power consumption

When we review the consumption of the entire system with the battery over the course of three minutes, we see that the base consumption of the device is 65mAh, with a peak of 180mAh when the data is sent via LoRaWAN.

We have to remark that although this application uses LoRaWAN, I would recommend moving up to a more energy-efficient (higher throughput per mW) cellular protocol like LTE-M or NB-IoT instead.

Nordic has the nRF9160 development kit and the Thingy:91 IoT prototyping platform in their catalog if you want to have ultimate compatibility.

The important part of this test is that I wanted an AI-intensive application to showcase the stability of the nPM1100. What we wanted to see in the graph is periods of stability with peaks at transmission, then returning to stability. And that's exactly what we got if you look down below. So, the nPM1100 is optimal for these kinds of applications as well, if we compare it to commonly used battery regulators like the ones we had in the project without the nPM1100. The normal regulators manage a much greater range and do not bother with stability like the one we see below in the PPK2 data.

Data obtained by the PPK2.

Here is a video demo:

Use case #3: AgroNordic

For this third use case, we look at project "Agro Nordic," in which we created a sustainable platform of sensing and irrigation automation with predictive analysis that integrates device communication through BLE.

BLE connectivity

The use of BLE as a means of communication to any BLE gateway was essential because we wanted this project to use very little energy.

The Bluetooth Low Energy application inside nRF Connect for desktop shows communication is properly working using the configuration we made.

Here is a video demo: BLE - AgroNordic

Power consumption

When reviewing the device's consumption for three minutes in normal operating conditions, we see the base consumption is 10.7mAh, with a peak of 16.9mAh. The increase in consumption is not appreciable when reading the sensors, this makes the nPM1100 and its evaluation kit a great platform for managing the consumption of sensor-heavy applications such as this one.

Of course, when having a sensor-heavy project such as this use case, you need the battery to last as long as possible. We spend a lot of time thinking about which connectivity protocol (energy-efficient protocols like LTE-M or NB-IoT) to use. It is quite important to also think about the power management options because that is what will feed your sensors and ultimately sensors are what consume more power in the end. When I tested for battery time for this application in comparison with previous forms of this project, it lasted quite longer (approximately 150% more) than its predecessors.

See all the data obtained by the PPK2.

Here is a video demo:

Conclusion

The nPM1100 is a superb energy management platform to build projects on. It works well with energy-intensive applications (lots of sensors and AI applications), but excels at applications that require battery management and where battery life is of utmost importance.

These use cases let us test the feasibility of using the nPM1100 evaluation kit as a final power supply for device production.

Note, the "illegal logging and fire detector" consumes almost five times more energy than the other two use cases because it uses AI in addition to a microphone based on op-amps. However, it is preferable to use the nPM1100 evaluation kit due to its low power consumption and excellent voltage regulation, more because of the consumption peaks that it has. Despite the fact that the recommended limit of the module is 150mA, it did not have a problem with 180mA spikes.

We would not recommend this device when the consumption exceeds 150mA. This can occur when we connect too many peripherals to a microcontroller or when, despite having few peripherals, the MCU has intensive processing such as when running an AI model.

Why is the nPM1100 a good choice for this?

The nPM1100 evaluation kit has the particular advantage of being very compatible with the nRF52 or nRF53 Series SoC, so in the case of using the XIAO-board with the nRF52840, it provides us with greater certainty of a good result. In the case of our tests, the best consumption we found was ECG. By having a battery charge of up to 400mA, it allows its charge to be quite fast once the prototype is made. The voltage output between 3.3v - 1.8v enables us to power a large number of boards and MCUs on the market, since these usually have an operating voltage between 3.3v - 2.7v, not to mention that some FPGAs have a supply voltage of up to 3.3v - 1.8v.

Thank you for following this series and hopefully, this helps you integrate Nordic's nPM1100 into power manage your projects!