“The Internet of Things promises to bring major changes to the way we manage and interact with our homes and offices. In addition, it is expected to change the way companies provide services, especially in the commercial and industrial sectors, where capital-intensive equipment could previously be provided as services to customers. Although this concept is easy to understand, the impact of an organization with this in mind will largely depend on the continuous and reliable data collection of many different data elements. For a large number of wirelessly connected microcontroller-based sensors, this will be a job, with many battery operated and left in place for a long time.
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The Internet of Things promises to bring major changes to the way we manage and interact with our homes and offices. In addition, it is expected to change the way companies provide services, especially in the commercial and industrial sectors, where capital-intensive equipment could previously be provided as services to customers. Although this concept is easy to understand, the impact of an organization with this in mind will largely depend on the continuous and reliable data collection of many different data elements. For a large number of wirelessly connected microcontroller-based sensors, this will be a job, with many battery operated and left in place for a long time. Providing such sensor data will require the design and use of ultra-low-power wireless transceiver microcontrollers, which not only have extremely low-power standby current, but also use energy-saving technologies to extend the working life of a single button battery. These technologies can be implemented in hardware or software or a mixture of the two, but it is clear that designers need to consider many other broader factors before choosing a single device.
One of the key factors will be the selected wireless protocol. This is mainly determined by the amount of data transferred. Although Wi-Fi is a natural choice for moving large amounts of data, it consumes a lot of power. For typical sensing applications, it will use methods such as Bluetooth Smart and ZigBee, as well as other 802.15.4 sub-GHz technologies. . When selecting a device, the engineer should also understand the various aspects that make up the overall power consumption curve of the device. There is a balance between computing performance and power profile. You may use a more powerful device to provide more computing resources, even though it may consume more power in order to complete calculation and transmission tasks faster. Also, don’t forget that some communication stacks require the radio to run longer for a given packet, so it is not just a combination of the power consumption of the wireless MCU.
Figure 1: The ultra-low sensor controller operates independently of the rest of the device.
The SimpleLink CC26xx device family of Texas Instruments provides a variety of communication method options. The TI CC2650 device combines a 2.4 GHz Bluetooth Low Energy (BLE) v 4.1 compatible wireless transceiver, an ARM Cortex-M3 32-bit processor and an ultra-low power 16-bit sensor controller, which can provide as low as 2 standby power RTC It is 1μA during operation and RAM retention, as low as 100 nA in shutdown mode, and can be awakened by an external event. The CoreMark benchmark score is 141.85, CoreMark/MHz is 2.955 (CC2650-7ID device runs at 3.0 V and 48 MHz), the MCU consumes 61μA/MHz in working mode, and the active mode transmitter current is 9.1 mA, + 5 dBm output . The 16-bit sensor controller is responsible for keeping the radio transceiver asleep for as long as possible. By combining with external sensors such as analog comparators or ADCs, the sensor controller in Figure 1 is designed to operate completely autonomously, allowing the radio and 32-bit MCU to maintain an extremely efficient standby mode until it is needed to send data. Able to perform up to 10 ADC readings per second, with an average power consumption of less than 3μA, this method can be used in, for example, heart rate sensor applications. To do this, you can perform up to ten measurements per second, and then send all ten measurements at the same time. This energy-saving hardware method means that there is no need to wake up the radio and MCU for each measurement, which is equivalent to saving 10 times the power consumption (Figure 2).
Figure 2: Read the sensor 10 times before transmitting the data.
Another way to save power is to add a certain level of energy harvesting to the power supply. Silicon Labs uses this approach, using the Si1010 series of ultra-low power sub-GHz wireless microcontrollers. For example, Si1012 adopts high-speed 25 MIPS 8051 MCU and EZRadioPro transceiver, can work in the range of 0.9 to 3.6 V, and consumes as low as 0.1μA in deep sleep mode. It takes about 1μA to preserve the RTC and radio state. The deep sleep wake-up time is within 2μs. It is equipped with ADC, three GPIO pins and four GP counter/timers. It is an ideal device for IoT sensor applications. Being able to supply power from an energy harvesting source, it is expected that IoT sensors can be designed to have an expected life of 15 years without the need to replace thin-film batteries. In order to speed up the design using this method, Silicon Labs provides an energy harvesting reference board that can be used to fully prototype and demonstrate ultra-low-power sensor designs in practice (Figure 3). In addition to Si1012 devices, the board is also equipped with printed antennas, power management ICs and solar panels.
Figure 3: Silicon Labs energy harvesting sensor evaluation board.
When Si1012 is not transmitting data, it can remain in a very low power consumption state equivalent to approximately 50 nA. Only 50 lux of light is needed to compensate for the solar panel leakage current and start charging the thin-film battery. Only thin-film batteries can provide enough energy for wireless transceivers and sensors for about seven days. Indoor lights usually provide up to 200 lux, while outdoor conditions will provide up to 10,000 lux, enough to keep the battery charged and provide power. Figure 4 shows the possible duty cycle and energy consumption of an example IoT sensor application that transmits data per second.
Figure 4: Energy consumption curve Si1012.
Managing the energy-efficient wireless communication of sensors can also be the job of fine-tuning software. This method requires a detailed understanding of the ongoing process in the MCU and wireless transceiver at any time. It should also be noted that in some cases, developers should also check whether any compiler optimization options, such as “optimization time”, should be fully utilized. A series of codes can be executed faster, the longer the device can stay in sleep mode. The IDE tool chain increasingly provides the ability to monitor energy consumption during debugging, further helping the design to reduce energy consumption as much as possible. Atmel ATmega256RFR2 series ZigBee/802.15.4 wireless transceiver is an example, which provides a set of published software technologies designed to adaptively reduce power consumption below the normal prescribed limit. The device uses an Atmel 8-bit AVR MCU core and a low-power 2.4 GHz transceiver designed for ZigBee/802.15.4. It is powered by a 1.8 to 3.6 VDC power supply and has a deep sleep power consumption of less than 700 nA. The sending current of MCU and transceiver is 18.6 mA. Figure 5 shows the different total power consumption of the available modes.
Figure 5: Atmel ATmega2564RFR2 wireless MCU power/sleep mode configuration file.
Atmel Intelligent Power Reduction Technology Application Note records a set of reduced power consumption (RPC) software technologies that are independent, self-calibrating, and adaptive power reduction solutions. One of the solutions is the PLL energy-saving mode. This mode helps to automatically switch to power saving mode immediately after PLL calibration, thereby reducing power consumption. This method is documented in more depth in the application note, which can reduce the power consumption of the device from 5.2 mA to 450 μA. Another technology is Smart Receiving Technology (SRT), in which the transceiver can be periodically enabled and disabled while monitoring incoming data frames. According to environmental conditions, data traffic and channel noise, SRT mode can save up to 50% of current consumption, but this will result in a small loss of sensitivity.
The Internet of Things will rely on countless battery-powered wireless sensors, which are usually deployed in remote areas or difficult to access locations in large factories. When you consider visiting the location on a regular basis, the cost of replacing cheap button batteries will increase significantly, not to mention the possible interference to the IoT analysis and control system during this period.
The time to implement energy-saving technologies, whether it is hardware, software or a hybrid of the two, will extend the service life between battery replacements and make the manufacturer’s sensor a cost-effective sensor on the market.
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