Development



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<h2> What are embedded systems? </h2>
Embedded systems are computer systems with a specific function within a larger system. This includes all computing systems, such as home appliances, digital watches, cameras, avionics, and medical devices, except for PCs and smartphones. When classifying embedded systems by their main computing component, two of the most common types are microcontroller (MCU) and a microprocessor (MPU/CPU) based systems. There are also DSP, FPGA and custom ASIC-based systems. 


Microcontroller-based embedded systems are typically programmed either without an operating system, known as "bare metal," or with a real-time operating system (RTOS). Microcontrollers are cost-effective, single-chip computers that include a CPU, memory, and input/output capabilities on a single integrated circuit (IC). However, their specifications are limited compared to standard PCs, with less than 1MB of RAM and less than 8MB of flash memory, and typically only one CPU core with a frequency of less than 500MHz. Many 32-bit microcontrollers today are based on ARM Cortex-M CPUs.

In contrast, microprocessor-based systems, which are based on more powerful CPUs such as ARM Cortex-A, run Linux and have specifications more similar to PCs or smartphones. These systems, known as single-board computers, feature RAM, eMMC (flash), and various peripheral chips on the board, rather than on a single IC.

![1.png](https://strapi.suprabit.eu/uploads/1_a622eb8f94.png)

While microcontroller-based systems are generally more affordable and energy-efficient than embedded Linux devices, they also have more limited computing capabilities and feature sets. This blog post will focus on the unique characteristics of microcontroller-based embedded systems. However, as part of the Internet of Things (IoT) ecosystem, modern embedded systems are expected to have a range of features such as wireless communication, internet connectivity, and advanced sensors and actuators, all while maintaining cost and power efficiency. Careful consideration of both hardware and software is crucial for the successful design and development of these devices.

<h3> Optimizing power consumption </h3>
When selecting components for a wireless embedded device, it is important to consider factors such as suitability for the intended application, software and community support, market availability and cost. The microcontroller, RF communication chip, and sensors/actuators are the main components to evaluate. Factors like deep sleep functionality, communication interfaces, security options, processing speed, and memory of the microcontroller should all be taken into account to ensure that the device's requirements are met in the most optimal way possible.

<h3>MCU</h3>
Low-power MCUs on the market can typically achieve current consumption below 1 μA in their sleep modes. Some of these include ST's STM32L0xx, Silicon Labs' C8051F98x, Microchip's SAM Lx and TI's MSP430.
In our recent project, we used STM32L051 MCU and in its Stop mode, we were able to achieve 1.3 μA with Low Power Timer and Watchdog running.



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<h3> RF communication chip </h3>
When choosing an RF communication chip, it's important to select an appropriate wireless communication protocol that takes into account factors such as power consumption, range, and throughput. Factors that will affect the power consumption of the device are protocol frequency (sub-GHz, 2.4 GHz, 5 GHz, etc.), data packet length, the number of messages being sent within a certain timeframe, and signal power. Operating frequency affects range, power consumption, and throughput. Lower frequencies (sub-GHz) have better range and lower power consumption, while higher frequencies have better throughput. It's essential to keep the number of messages sent within a certain timeframe as low as possible for battery-powered devices, usually 1-2 messages every 10+ minutes. Smaller data packet length increases the throughput and power efficiency of a protocol, as it takes less time to transmit information and keeps the RF transceiver in active mode. With greater power, the range is increased, but so is power consumption. Low-power RF chips on the market can typically achieve current consumption in the nA or few μA range in their sleep modes, making them a good choice for battery-powered devices. In our recent project, we used AX5243 sub-GHz RF chip at 868 MHz with a custom protocol. In its Powerdown mode, we were able to achieve 0.8 μA.

![2.png](https://strapi.suprabit.eu/uploads/2_d19cc36535.png)
When choosing sensors/actuators, their idle current consumption should also ideally be in nA or worst-case few μA range.

Besides hardware, software choices and optimizations can also greatly affect the power consumption of a device; choosing the appropriate sleep mode of the MCU and RF chip, minimizing time spent in running mode of the MCU and RF chip, using only the lowest-power MCU timer while the device is in idle mode, setting MCU peripherals in low-power mode, etc.



<h5>Here are some important takeaways from our recent project with STM32L051:</h5>
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<li  style="color:#ffffff">setting all unused GPIOs as analog inputs has reduced average current consumption by a few μA</li>
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<li style="color:#ffffff">ADC needed to be powered off after each measurement, otherwise it would add ~35 μA to average current consumption in sleep mode </li>
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<li style="color:#ffffff">although Standby mode has the lowest current consumption, in this mode SRAM and register contents are lost and only certain GPIOs can wake up MCU, so we've used Stop mode</li>
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<li style="color:#ffffff">in Stop mode, LSI is the only oscillator that works (and only timers whose clock source is LSI can work</li>
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<li style="color:#ffffff">LSI is unprecise, but it can be calibrated using an internal MSI oscillator and more precise e.g. periodic interval measurements can be achieved</li>
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Wireless embedded devices transmit data in periodic intervals and spend the rest of the time in sleep mode, which minimizes the amount of time the microcontroller and RF transceiver are running and consuming power. However, if the running time is too long, it can significantly impact the average power consumption and shorten the device's battery life. To optimize power consumption, it's important to keep the duration of running time to a minimum, whether due to a periodic interval or an interrupt.


<h5>Here are some methods that we've used to minimize the duration of running time: </h5>
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<li  style="color:#ffffff">compiler optimizations</li>
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<li style="color:#ffffff"> removing printfs/serial outputs  </li>
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<li style="color:#ffffff">making sure there's no polling or register flag checking that keeps device in running mode</li>
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<li style="color:#ffffff">checking whether higher MCU frequency (with higher current consumption, but shorter processing time) is better for power consumption</li>
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<li style="color:#ffffff">using constants/hard coded values instead of calculations if possible</li>
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It's important to select an RTOS mode that is optimized for low power consumption, especially as the number of features increases, as RTOS is often required in such cases.

Finally, tools that we've used to measure current consumption are Otii Arc and a multimeter (just to double-check Otii Arc measurements). Also, it's useful to have measurement ports on PCB for measuring the current consumption of certain components separately (MCU, RF transceiver, sensors).

![pic1.png](https://strapi.suprabit.eu/uploads/pic1_6e7794a3ee.png)


With whole PCB average current consumption being under 5 μA (idle mode consumption below 2.5 μA), these devices can ideally last on one e.g. CR2032 battery (~230 mAh) for more than 5 years.

<h2> Optimizing memory usage </h2>
As projects need to be profitable, prices of the components are very important. But with lower prices, MCUs usually also come with smaller amounts of RAM and Flash memory. For example, STM32L051 has 8 kB of RAM and 64 kB of Flash memory . As the complexity of the application increases and the feature set expands, optimizing memory usage becomes necessary for these microcontrollers.

<h5>Here are some methods of optimizing memory usage that we've used in our recent project: </h5>

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<li  style="color:#ffffff">compiler flags</li>
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<li style="color:#ffffff; opacity: 70%;">we've used GCC's <span style="font-weight:bold">arm-none-eabi</span> toolchain: <span style="font-weight:bold">-ffunction-sections, -fdata-sections, -fno-exceptions, -fno-rtti, -Os, --specs=nano.specs</span> (for using nano version of newlib)</li>
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<li style="color:#ffffff">check out functions with the highest memory usage and try to optimize them</li>
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<li style="color:#ffffff; opacity: 70%;">for <span style="font-weight:bold">arm-none-eabi</span> toolchain: <span style="font-weight:bold">arm-none-eabi-readelf -s elf_name.elf</span></li>
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<li style="color:#ffffff"> disable unused RTOS features</li>
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<li style="color:#ffffff">remove unnecessary printfs</li>
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<li style="color:#ffffff">remove double and float arithmetic <span style="font-weight:bold">__aeabi_</span>functions if possible</li>
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That wraps up this blog post on memory and power consumption optimization for microcontroller-based embedded systems. We hope it'll turn out to be helpful in your current and future embedded projects too!

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In this blog post, we'll explore various ways of optimizing power consumption and memory usage of wireless embedded devices with examples from one of our recent projects.

Optimizing power consumption and memory usage of wireless embedded devices

Blockchain


## Motivation
Modern Smart Building Management solutions are fairly complex, comprising of a number of software modules supporting a variety of, often proprietary, protocols. When you add in all the front and back-end devices, automation stations, sensors and gateways, it can all seem like a real pain in the neck. But there is a clear economic benefit as functional smart building solutions are able to optimize energy consumption, provide better living environments and better security for building occupants, bringing your business closer to achieving that net zero goal. However, there are new issues regarding data security popping up every day, due to complexity, Internet integration and, more often than usual, slow adaptation to the newest technology stack. Traditional solutions relied on private networks where security was not such a big deal, but now, as every smart building solution provider offers Internet connectivity, the security paradigm changed. That left most solutions vulnerable to inside and outside attacks as well as data breaches. On the other hand, with the advancement of the Internet, many new use cases emerged that have the potential to significantly improve the ROI of smart building management solutions and enable more building automation in favour of building occupants and investors.  

This presents an obvious need to introduce a new data infrastructure layer to your solutions that will guarantee data security and data availability within a smart building management market. 

## Lavsa
Lavsa is a decentralized storage solution for smart building management, developed using blockchain and IoT technology. Our solution is taking in a stream of data and then replicating that data to every node in a private blockchain network. The newly added data sets are hashed and the hash is published on permissionless public blockchains like Ethereum, Polygon etc. By using blockchain(s) as an additional layer of security, we are improving integrity, immutability and availability. This is a step up from the traditional database model because, in Lavsa, every piece of data is distributed across a number of nodes and additionally hashed on a public blockchain, making it virtually impossible to fake, change or delete the data. At the same time, smart contracts are used to improve data relevancy, white and black lists and support new use case scenarios.  




![blockchain.svg](https://strapi.suprabit.eu/uploads/blockchain_77fbf6c69c.svg)





## Lavsa Goals
- Put the building data security, integrity and availability at the forefront of the Smart Building and IoT initiatives
- Establish trust among stakeholders of the building automation projects
- Enable higher level of automation
- Support integration with third-party building automation and business solutions
- Enable new disruptive business models 
 

## Lavsa Use Cases

Lavsa puts the data produced by a variety of smart building devices at the forefront of the Smart Building economy enabling new disruptive business models like 
- Data monetization and data markets
- AI solutions based on relevant building data
- Regulatory compliance
- Support for ESG initiatives 
- M2M payments
- Building Automation Infrastructure As a Service

If you have any questions regarding Lavsa, or if you are interested in discussing various Smart Building use cases - feel free to [contact us](https://suprabit.eu/contact) and let's give it a thought together.



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Back in 2018., the blockchain hype started to gain traction outside of the crypto scene and a number of enthusiasts proposed using blockchain for different business use cases. We had a vision to provide every party with relevant and tamper-proof data delivered by smart building sensors and devices. That data has to be so good that somebody wants to pay for it. Once you bought it, you want to have it ready at your disposal for further processing. And you want to be sure of its integrity.

Optimizing power consumption and memory usage of wireless embedded devices

Lavsa - a new kid on the Block