Optimizing Embedded Systems for IoT Applications

Embedded systems are specialized computing devices integrated within larger systems to perform dedicated functions.

In IoT applications within industrial automation, we generally optimize embedded systems for several reasons. In this article, we will look at some of them and discuss the strategies and techniques to achieve each objective.

Hardware and Resource Utilization

The hardware you choose significantly affects attributes like power consumption and processing capabilities of the system which in turn affect the efficiency of your IoT device. Therefore, the hardware components you choose must be optimized. Factors to consider in proper hardware selection include:

• The processor (CPU): This will dictate the system’s power and energy efficiency. Therefore, in IoT applications where power consumption is critical, low-power microcontrollers (MCUs) or system-on-chip (SoC) solutions are the best.

ARM Cortex-M series processors are also commonly used because of their low power consumption, wide availability, and strong ecosystem support. You can choose within this series based on factors like required processing power, peripherals, and cost constraints.

If you are dealing with more compute-intensive applications, ARM Cortex-A series processors or low-power variants of x86 processors may be more suitable although at the expense of more power.

• Memory: Memory requirements depend on the complexity of the application like the size of the firmware, data storage needs, and processing demands.

Use flash memory with sufficient capacity for firmware storage and overprovision it to accommodate firmware updates and data logging. Consider using low-power flash memory like NAND or NOR flash for energy efficiency.

While RAM requirements vary widely based on the application needs, select low-power RAM modules or integrate RAM into your processor of choice to minimize power consumption.

• Wireless Connectivity: Since IoT devices heavily rely on wireless connectivity for communication with other devices and services, wireless connectivity optimizations must be made to ensure reliable communication.

Consider selecting wireless protocols based on the specific requirements of the application like indoor vs. outdoor deployment, data throughput, and power constraints.

If interoperability is something you are considering for your application, then use integrated solutions combining wireless protocols, such as Wi-Fi and Bluetooth.

• Sensors and Peripherals: Your IoT systems will likely require sensors and peripherals like motion potentiometers to collect data from the environment or interface with external devices. This is why you must consider the accuracy, power consumption, and interface compatibility when selecting sensors to use.

Low-power sensor modules like MEMS-based accelerometers, gyroscopes, and environmental sensors, are common in IoT devices. Integration of sensor interfaces (e.g., I2C, SPI) into the chosen processor can simplify hardware design and reduce power consumption.

Power Efficiency
Since embedded devices in IoT applications often operate on battery power or have limited power sources, power optimization prolongs the battery life and allows the devices to work longer without recharging or replacing batteries frequently.

Here are several ways to make power-efficient embedded systems for IoT applications:

• Low Power Design:
  Always use energy-efficient components like microcontrollers, sensors and communication modules, and optimize the hardware and software to minimize power during active and idle states.

• Dynamic Power Scaling:
  Implement dynamic scaling so that the embedded systems can adjust their performance and power consumption based on workload and environmental conditions.

• Sleep Modes and Wake-up Mechanisms:
  Embedded systems can enter low-power sleep modes where non-essential components are turned off or placed in a low-power state. Wake-up mechanisms, such as interrupts from sensors allow the system to quickly transition from sleep to active mode when needed.

• Energy Harvesting:
  Consider using energy from the surrounding environment, such as solar, thermal, or kinetic energy whenever possible. The harvested energy can be stored in batteries or capacitors to power the embedded system.

• Efficient Communication Protocols:
  Use efficient high-speed digital design techniques, communication protocols, and other optimized data transmission strategies, such as reducing packet size, aggregating data, or utilizing low-power wireless technologies like Bluetooth Low Energy (BLE) or LoRaWAN, to minimize power usage.

• Predictive Analytics and Machine Learning:
  Employ predictive analytics and machine learning algorithms to analyze sensor data and predict future events or trends. This helps embedded systems to optimize their power management strategies more efficiently.

• Power Profiling and Optimization:
  Using techniques such as energy profiling tools and power-aware debugging can help developers pinpoint power-hungry components or code segments that need optimization.

Real-time Responsiveness
Most IoT applications are designed for real-time processing and response to events or data inputs. To achieve this, real-time operating system software (RTOS) is used and therefore, to optimize the real-time responsiveness of an embedded system, this is the software that must be optimized.

You can simply do this by using lightweight RTOS or embedded Linux distributions tailored for IoT devices. These operating systems have several advantages for real-time IoT applications like:

• Deterministic Timing:
  RTOS ensures that tasks are executed within specific time constraints, which is essential for maintaining system stability and reliability.

• Resource Efficiency:
  RTOS are typically lightweight and optimized for resource-constrained environments. They efficiently manage system resources, allowing IoT devices to operate within their constraints while still meeting performance requirements.

• Task Scheduling:
  In IoT applications, where multiple tasks need to be performed concurrently, efficient task scheduling must be done to optimize system performance and responsiveness and RTOS can do this.

• Power Management:
  RTOS often includes power management features to minimize energy consumption without sacrificing performance.

• Communication Protocols:
  RTOS has built-in support for communication protocols, simplifying the development of IoT applications and ensuring seamless interoperability between devices.

• Security
  : RTOS can incorporate security features such as memory protection and secure boot mechanisms to safeguard IoT devices against unauthorized access and other security risks.

• Scalability:
  These systems are designed to be scalable, allowing them to accommodate the evolving needs of IoT deployments without requiring significant changes to the underlying software architecture.

Cost Effectiveness
In commercial IoT deployments, cost optimization is all about delivering reliable performance and functionality at an affordable price. Without this, embedded systems in IoT devices cannot be economically viable for mass deployment.

You can optimize costs by considering hardware and software options, scalability, security, lifecycle management, and total cost of ownership.

Other Industrial Automation Objectives to Consider

• Reliability and Fault Tolerance:
  As industries evolve, we increasingly rely on Industrial processes that operate continuously without failure. That is why you must design embedded systems with redundancy, error detection, and fault tolerance mechanisms to ensure reliable performance even in challenging environments.

• Interoperability:
  Ensure that embedded systems support industry-standard communication protocols and interoperability standards to facilitate seamless integration with existing infrastructure since industrial IoT environments typically involve a mix of devices from different vendors.

• Remote Management and Monitoring:
  Enable remote management and monitoring capabilities for IoT devices that may be spread across large geographical areas so that administrators can monitor device health, perform updates, and diagnose issues without needing physical access to the devices.

• Environmental Considerations:
  Select components and enclosures that can withstand extreme industrial environment challenges without compromising performance or reliability.