When it comes to sensing our environment, it is of great interest to minimise power consumption. Not only does the production of energy affect our climate negatively, but reducing power consumption also creates opportunities in new markets.
In a time when air quality is becoming one of our largest global issues, interpreting what we measure is more relevant than ever. Measuring helps us make better choices both for our planet and for our own health and safety. Lowering the energy consumption of sensors does not only have an impact on the economic aspect of energy saving, but it also creates new market opportunities that can radically improve our decision-making.
The progress of IoT has increased at the same rate as more things start to communicate with each other. As collecting data in cloud-based solutions has become more popular, the market has recognised the advantage of having more measurement points. Also, customers are expressing a need for battery-powered solutions.
A battery-powered device creates a multitude of opportunities. The sensor battery can be recharged by energy harvesting of ambient energy (solar, thermal, wind, or any other green energy source). This means that we can now multiply our measurement points without further impact on the environment and that sensors can be placed at sites where there is no fixed power supply.
But does this come at a cost?
It might. There is a fundamental relationship between invested power and measurement resolution in all electronic sensors: the more electrical energy you invest in the measurement, the more accurate the reading will be. Therefore, obtaining high-resolution measurements using a low power sensor is a challenge.
The accuracy of a sensor reading is limited by systematic and random errors. The systematic errors are determined by the stability of the optics, the quality of the calibration, systematic errors in the electronics and the quality of the algorithms used. These errors are not related to electrical power. Instead, it is the quality of the material in the sensor and the skill of the sensor manufacturer that are factors.
On the other hand, the random error is directly linked to the power we put into the sensor. The nature of this error, called electrical noise, is random. Every time a measurement is made, the detection electronics "roll a dice" and add a random number to the measurement. If two sensors were used, the average result of the two could be used as the measurement value in order to reduce the random error. This solution works, but you would need double the power.
Another way to obtain the same result without the additional hardware is to turn on the infrared light source of the sensor and make measurements twice as often. Improvements in resolution, or reduction of noise, are made possible by taking the average of two measurements. But still, powering up the light source twice as often doubles the power used for light generation. From statistical arguments, we find that the resolution is proportional to the square root of invested power. Hence, when reducing the power, the resolution will get worse in proportion to the square root of the power. That means that if we want to reduce power consumption 100 times, the resolution will be 10 times worse.
Another way to trade power and resolution is by signal strength. Since the noise is generated by the detection electronics, we can gain resolution by increasing signal strength. Let us posit that if we double the light flux from the light source, we will get twice as much signal with the same noise. This will result in twice the resolution. If light power is reduced 100 times, the resolution will also be reduced 100 times.
When optimising for low power, the skilled sensor designer will first choose low noise components for detection electronics and optimise the optical design for a maximised signal. After that, the light, source power, and measurement duty cycle must be traded to fulfil the requirements of the resolution, battery life, and measurement period.
To maximise the outcome of this market opportunity by reducing the environmental impact (and at the same time saving money), there are three things you need to consider: the power consumption, the accuracy of the reading, and the life span of your sensor. Make sure you go with a supplier who understands all three of these criteria.
Senseair's expertise allows us to choose the most optimal sensing setups, especially for low-power sensors, whether by our strong irradiating incandescent emitter in the LP8, or the super-efficient LED emitter in the Sunrise. By knowing the pros and cons of both, we can offer our customers the best possible solution.