Embedded Systems: Heartbeat of IoT Devices

To retain a competitive edge, companies are rethinking their approaches to their processes, which marked the start of Industry 4.0. IoT. One of the life-changing technologies that is at the forefront of the new world is the Internet of Things (IoT). IoT revolves around the automation of processes, real-time data collection, and data-driven decision-making. IoT devices are meant to enhance the everyday lives of consumers as well as revolutionize the way companies in different industries operate.

According to Statista, revenue in the global IoT market is expected to have an annual growth rate (CAGR 2023-2028) of 13.60%. For comparison, the global telecom equipment market CAGR is 6,9%, smartphone market — 4.10%, and Big Data — 11,0%.

The growth of the IoT market is fueled by the development of complementary technologies. Over the years, the processing power of IoT devices significantly increased, making them more reliable and “smart”. Moreover, the sensors, which are widely used in IoT devices for data gathering, are becoming more advanced and, at the same time, affordable. And the introduction of 5G communication technology will improve the speed of connection between devices, which will result in a smoother user experience.

At the core of the interconnected world of IoT lies the concept of embedded systems. Embedded systems are a combination of hardware and firmware. The role of an embedded system is similar to that of a brain. It gathers the information from “sense organs” (sensors), processes it, and sends signals to the “body” (devices). These systems are essential for making IoT devices smart, efficient, and interconnected.

What Is IoT?

The term “IoT” stands for the “Internet of Things,” and it’s a lot more than just the embedded hardware and software that power your devices. It’s a vast network of interconnected devices that communicate and share data to enhance efficiency and provide insights. At its core, IoT is about gathering data and making sense of it to improve the way we make decisions.

IoT devices can be found across several industries, changing the way they operate. Here are examples of common IoT devices:

Healthcare: Wearable Health Monitors, Remote Patient Monitoring.
Smart Home: Smart Thermostats, Smart Locks, Smart Lights.
Manufacturing and Industry: Industrial IoT Sensors, Predictive Maintenance Sensors, and Asset Tracking Tags.
Agriculture: Precision Agriculture Sensors, Livestock Monitoring.
Logistics and Transportation: GPS Trackers, Fleet Management Systems.
Energy and Utilities: Smart Meters, Grid Sensors.
Retail: RFID Tags, Beacon Technology, Electronic Shelf Labels (ESL).
Smart Cities: Traffic Management Systems, Environmental Sensors, Waste Management.
Environmental Monitoring: Weather Stations, Water and Air Quality Sensors.
Security and Surveillance: Smart Cameras, Smart Alarms.

What Makes a Device “Smart”?

What elevates a device to the label of “smart”? A smart device is an embedded device that has the ability to collect and process data, make decisions, and take actions based on that data. It is typically connected to a network, and it can communicate with other devices and systems. The key characteristics of a “smart” device include:

Connectivity

Smart devices excel at seamless communication with other devices and systems. They are not isolated. Instead, they actively take part in a network, exchanging data with other connected devices. Many smart devices are cloud-connected, which allows them to store data, receive updates, and provide remote access. This cloud connectivity enhances their capabilities and enables users to access their devices from anywhere.

Data Sensing and Collection

Smart devices should be equipped with a variety of sensors. These sensors can range from temperature and humidity sensors to motion detectors, cameras, and even more specialized sensors, depending on the device’s purpose. They continuously collect data from their surroundings.

Data Processing and Analysis

Smart devices often have onboard processing power, allowing them to perform real-time data analysis without relying on external servers or the cloud. Some smart devices utilize machine learning and artificial intelligence algorithms to analyze data and generate insights. For instance, a smart device can combine data from multiple inputs and make appropriate decisions or generate alerts, showcasing its ability to utilize machine learning and artificial intelligence algorithms for enhanced functionality.

Real-time Responsiveness

Smart devices are capable of making immediate decisions and taking actions based on the data they collect. They can operate autonomously, executing predefined tasks without direct human intervention. For example, a smart irrigation system can adjust watering schedules based on real-time weather data and soil moisture. This automation streamlines processes and enhances efficiency.

Remote Monitoring and Control

Smart devices offer remote access through user-friendly interfaces, such as smartphone apps or web portals. This allows users to monitor device status, receive notifications, and control device functions from a distance. Users have greater control over their environments, whether it’s adjusting the thermostat while at work or checking home security cameras while on vacation.

The Role of Embedded Software in IoT Devices

At the core of every IoT device lies embedded software, which can be described as the “brain” that drives the device’s functionalities. Embedded software fuels data processing, facilitates interactions with sensors, and establishes communication protocols that enable devices to function seamlessly within complex ecosystems.

Every single person interacts with dozens of devices with embedded systems every day, often without being aware of it. Ensuring their seamless operation is an important task, as struggling with poorly designed devices can be frustrating and hinder the overall user experience.

Therefore, it is crucial for the embedded software to be developed by industry experts. Well-engineered software ensures that IoT devices operate smoothly, and provides intuitive interfaces, creating a simple and hassle-free user experience. Moreover, robust software maximizes the efficient usage of device resources, extending their lifespan.

Embedded software plays a key role in ensuring the success of IoT devices, contributing in the following key areas:

Reliability: Embedded software ensures the reliable and consistent performance of IoT devices, even under challenging conditions.
Security: Embedded software safeguards data integrity and device security, which is of major importance in the IoT landscape where data breaches can have serious consequences.
Efficiency: Given the constraints of IoT devices, particularly in terms of processing power and memory, embedded software works towards optimizing resource utilization.
Flexibility: The adaptability of IoT devices to changing requirements is enabled by the flexibility of embedded software.
Interoperability: Embedded software guarantees smooth interactions between devices, regardless of the manufacturer, enabling a cohesive ecosystem.

Challenges in Developing Embedded Software for IoT Devices

While the potential of IoT devices is immense, the successful development of embedded systems is challenging. According to Beecham Research, nearly three-fifths (58%) of businesses reported unsuccessful IoT projects. This is due to the lack of experienced companies in embedded software development that are able to overcome the challenges that IoT projects possess.

Some of the most common challenges that stand before IoT developers are the following (listed by priority):

Hassle-Free User Experience: Creating intuitive and consistent interfaces for diverse IoT devices, including touchscreens and voice recognition, presents design and testing challenges, complicating user experience design.
Reliability in Wireless Communication: Overcoming signal interference, latency, and dropout issues in wireless communication is essential for device reliability, particularly for battery-powered IoT devices.
Optimizing for Limited Resources: Efficient software development within limited processing power and memory constraints makes code and memory optimization a necessity, especially when planning for feature expansion.
Interoperability: Developing software compatible with various IoT protocols and network conditions demands extensive compatibility testing and security measures while maintaining interoperability.
Security and Privacy Concerns: Ensuring robust data protection with encryption and access controls is crucial, as well as compliance with privacy regulations to build trust and avoid legal complications.
Hardware-Software Interactions: Coordinating interactions between hardware and software requires in-depth knowledge of both domains, adding complexity to the development process.
Scalable Architecture: Designing software with scalability in mind allows for future updates and expansions without major reengineering, ensuring optimal performance as IoT ecosystems evolve.
Power Efficiency: Maximizing power efficiency is critical, especially for battery-powered IoT devices. This includes optimizing the software to minimize energy consumption during both active and idle states.
Firmware Updates: Implementing a secure and reliable mechanism for over-the-air (OTA) firmware updates can be challenging. The updates shouldn’t disrupt device operation or introduce vulnerabilities.
Real-Time Requirements: Some IoT applications, such as industrial automation and autonomous vehicles, require real-time processing and low-latency responses. Meeting these timing requirements can become an issue.
Data Management: Handling and processing large volumes of data generated by IoT devices is part of their nature. Effective data storage, retrieval, and analysis strategies are needed to make the most of IoT-generated data.
Compliance and Certification: Depending on the industry and application, IoT devices may need to adhere to specific standards and certifications. Moreover, it is essential to stay up-to-date with legal and regulatory requirements related to IoT devices, such as data protection and cybersecurity laws, to avoid legal issues.
Testing and Debugging: Testing embedded software for IoT devices is complicated by limited access to hardware and the need for specialized testing equipment. Debugging issues can also be more complex in embedded systems.
Longevity and Maintenance: IoT devices are often expected to have long lifespans. Ensuring that software remains secure, functional, and compatible with evolving technology over an extended period is a priority during development.

All of these challenges can be easily avoided by partnering with companies that have extensive knowledge of embedded systems development.

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Conclusion

In the expanding landscape of IoT, embedded software stands as the cornerstone of innovation. The fusion of hardware and firmware allows IoT devices to achieve their full potential, offering outstanding connectivity, intelligence, and convenience. By understanding the ins and outs of embedded software development, we pave the way for a more interconnected, secure, and data-driven world.

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Modern manufacturing machines are typically equipped with IoT sensors that capture performance data. AIoT technology analyzes this sensor data, and based on vibration patterns, the AI predicts the machine's behavior and recommends actions to maintain optimal performance. This approach is highly effective for predictive maintenance, promoting safer working environments, continuous operation, longer equipment lifespan, and less downtime. Additionally, AIoT enhances quality control on production lines.

For example, Sentinel, a monitoring system used in pharmaceutical production by IMA Pharma, employs AI to evaluate sensor data along the production line. The AI detects and improves underperforming components, ensuring efficient machine operation and maintaining high standards in drug manufacturing.

IoT devices - from fleet vehicles and autonomous warehouse robots to scanners and beacons - generate large amounts of data in this industry. When combined with AI, this data can be leveraged for tracking, analytics, predictive maintenance, autonomous driving, and more, offering greater visibility into logistics operations and enhancing vendor partnerships.

Example: Amazon employs over 750,000 autonomous mobile robots to assist warehouse staff with heavy lifting, delivery, and package handling tasks. Other examples include AI-powered IoT devices such as cameras, RFID sensors, and beacons that help monitor goods' movement and track products within warehouses and during transportation. AI algorithms can also estimate arrival times and forecast delays by analyzing traffic conditions.

IoT sensors monitor movement and customer flow within a building, while AI algorithms analyze this data to offer insights into traffic patterns and product preferences. This information enhances understanding of customer behavior, helps prevent stockouts, and improves customer analytics to drive sales. Furthermore, AIoT enables retailers to deliver personalized shopping experiences by leveraging geographical data and individual shopping preferences.

For instance, IoT sensors track movement and customer flow, and AI algorithms process this information to reveal insights into traffic patterns and product preferences. This ultimately leads to better customer understanding, stockout prevention, and enhanced sales analytics.

Recent research by Continental reveals that over 27% of surveyed farmers utilize drones for aerial land analysis. These devices capture images of crops as they are and transmit them to a dashboard for further assessment. However, AI can enhance this process even further.

For example, AIoT-powered drones can photograph crops at various growth stages, assess plant health, detect diseases, and recommend optimal harvesting strategies to maximize yield. Additionally, these drones can be employed for targeted crop treatments, irrigation monitoring and management, soil health analysis, and more.

Smart cities represent another domain where AIoT applications can enhance citizens' well-being, facilitate urban infrastructure planning, and guide future city development. In addition to traffic management, IoT devices equipped with AI can monitor energy consumption patterns, forecast demand fluctuations, and dynamically optimize energy distribution. AI-powered surveillance cameras and sensors can identify suspicious activities, monitor crowd density, and alert authorities to potential security threats in real-time, improving public safety and security.

For example, an AIoT solution has been implemented in Barcelona to manage water and energy sustainably. The city has installed IoT sensors across its water supply system to gather water pressure, flow rate, and quality data. AI algorithms analyze this information to identify leaks and optimize water usage. Similarly, smart grids have been introduced to leverage AI to predict demand and distribute energy efficiently, minimizing waste and emissions. As a result, these initiatives have enabled the city to reduce water waste by 25%, increase renewable energy usage by 17%, and lower greenhouse gas emissions by 19%.

Integrating AI and IoT in healthcare enables hospitals to deliver remote patient care more efficiently while reducing the burden on facilities. Additionally, AI can be used in clinical trials to preprocess data collected from sensors across extensive target and control groups.

For example, intelligent wearable technologies enable doctors to monitor patients remotely. In real-time, sensors collect vital signs such as heart rate, blood pressure, and glucose levels. AI algorithms then analyze this data, assisting doctors in detecting issues early, developing personalized treatment plans, and enhancing patient outcomes.

The smart home ecosystem encompasses smart thermostats, locks, security cameras, energy management systems, heating, lighting, and entertainment systems. AI algorithms analyze data from these devices to deliver context-specific recommendations tailored to each user. This enables homeowners to use utilities more efficiently, create a personalized living space, and achieve sustainability goals.

For example, LifeSmart offers a comprehensive suite of AI-powered IoT tools for smart homes, connecting new and existing intelligent appliances and allowing customers to manage them via their smartphones. Additionally, they provide an AI builder framework for deploying AI on smart devices, edge gateways, and the cloud, enabling AI algorithms to process data and user behavior autonomously.

When your product is successfully launched and available on the market we provide ongoing support and maintenance services to ensure your product remains competitive and reliable. This includes prompt resolution of any reported issues through bug fixes and updates.

We continuously enhance product features based on user feedback and market insights, optimizing performance and user experience.

Our team monitors product performance metrics to identify areas for improvement and proactively addresses potential issues. This phase aims to sustain product competitiveness, ensure customer satisfaction, and support long-term success in the market.

Our software team focuses on completing the full product feature range, enhancing the user interface and experience, and handling all corner cases. We prepare product software across the whole lifecycle by providing all necessary procedures, such as manufacturing support and firmware upgrade.

We also finalize the product's hardware design to ensure robustness, scalability and cost-effectiveness.

This includes rigorous testing procedures to validate product performance, reliability, and security. We manage all necessary certifications and regulatory compliance requirements to ensure the product meets industry standards and legal obligations.

By the end of this phase, your product is fully prepared for mass production and commercial deployment, with all documentation and certifications in place.

Our development team focuses on implementing core product features and use cases to create a functional Minimum Viable Product (MVP). We advance to refining the hardware design, moving from initial concepts to detailed PCB design allowing us to assemble first prototypes. Updated documentation from the Design phase ensures alignment with current project status. A basic test framework is established to conduct preliminary validation tests.

This prepares the product for real-world demonstrations to stakeholders, customers, and potential investors.

This phase is critical for validating market readiness and functionality before proceeding to full-scale production.

We meticulously select the optimal technology stack and hardware components based on your smart product idea with detailed use cases and feature requirements (Market Requirements Document / Business Requirements Document). Our team conducts thorough assessments of costs, performance metrics, power consumption, and resource requirements.

Deliverables include a comprehensive Product Requirements Document (PRD), detailed Software Architecture plans, an Initial Test Plan outlining validation strategies, Regulatory Compliance Analysis to ensure adherence to relevant standards, and a Proof of Concept (POC) prototype implemented on breakout boards.

This phase aims to validate the technical feasibility of your concept and establish a solid foundation for further development.

If you lack a validated idea and MRD/BRD, consider utilizing our IoT Strategic Roadmap service to gain insights into target markets, user needs, and desired functionality. Having a structured plan in the form of an IoT Strategic Roadmap before development begins is crucial to mitigate complications in subsequent product development phases.

Embedded Systems: Heartbeat of IoT Devices

What Is IoT?