Building IoT Ecosystems with Open-Source Tools

When it comes to IoT development, one of the first decisions businesses need to make is the choice of technologies to use. Today, the popularity of open-source tools for building custom IoT ecosystems is growing. These solutions and tools are publicly available for use, modification, and distribution. Typically, they are developed and maintained by a community of developers and often come with source code. This means that anyone can inspect, enhance, or adapt the code to their needs.

In this article, we will explain the benefits of using open source IoT solutions for your projects and provide a step-by-step guide to help you better organize the development process.

The Internet of Things (IoT) ecosystem can be defined as a network of interconnected devices that operate and function within the same environment. These devices can communicate and exchange data to achieve specific goals.

There are various types of IoT ecosystems, including smart systems, smart homes, industrial IoT ecosystems, healthcare, and agricultural systems. While they may have different features and capabilities, all such solutions share certain key components. Let’s consider the most important of these.

Devices and Sensors

These are physical objects that interact within a system. Sensors collect data about the environment and measure its physical parameters. For example, some custom IoT ecosystems are designed to gather information on temperature, air humidity, or people flow. Sensors translate physical phenomena into a digital format.

Devices encompass a broader category, including sensors, gateways, and actuators. Actuators perform actions based on commands received from sensors. For instance, if the temperature in a room falls below a set level, an actuator-driven heating system will automatically turn on.

Connectivity and Networks

This component constitutes the communication layer of the ecosystem, enabling data transfer between devices and other parts of the system. Connectivity is typically ensured by protocols such as Wi-Fi, Bluetooth, or cellular networks. Additionally, low-power wide-area networking (LPWAN) protocols like LoRaWAN, Zigbee, or Z-Wave are used in industrial and large-scale IoT deployments where energy efficiency is critical.

Data Processing and Analytics

The functioning of IoT ecosystems relies not only on data collection but also on processing and analysis. Efficient data processing and the ability to send commands based on analysis are crucial.

To reduce latency and bandwidth usage, data processing is often performed at the edge, closer to where the data is generated. In some cases, fog computing is used, operating between the cloud and edge layers to balance the two.

User Interfaces and Applications

Applications with graphical user interfaces (GUIs) enable remote control and management of IoT devices. A simple example is an app that allows users to interact with their smart home system.

Why do so many companies prefer to rely on open-source options for building their custom IoT systems? Let’s take a closer look at the advantages of such tools.

• Cost efficiency. Open source IoT platforms and other components are often free to use. This helps to reduce development and operational costs compared to the use of commercial proprietary tools.
• Customization. Open source IoT solutions can be modified. This makes it possible to create custom IoT ecosystems that will meet specific business needs.
• Transparency. The transparent nature of the open-source code lets developers conduct thorough audits. It means that they can timely identify and quickly fix security vulnerabilities.
• Community support. Open source IoT solutions often can boast great popularity. As a result, they have rather big and active communities. Developers who work with such tools are ready to share their knowledge and provide recommendations to the teams that need help.
• Interoperability. As a rule, such tools support open standards. Thanks to this, it is not very complicated to integrate various IoT devices and systems provided by different vendors.

Today the market offers quite a lot of open source IoT platforms and tools that can be used for building your custom system. Of course, they may differ in quality and security. That’s why while making a choice, you should be very attentive. Let us share with you the list of tools that we rely on in our work.

Hardware platforms

• Arduino. It is one of the most popular options for open-source IoT projects. It provides a variety of microcontroller boards, each equipped with digital and analog input/output pins. They can be seamlessly connected to different sensors, actuators, and other electronic components. Apart from easy-to-use hardware, Arduino also offers software that includes two types of integrated development environments, as well as the Arduino IoT Cloud service.
• Raspberry Pi. This credit-card-sized computer works on the basis of an ARM processor and is able to run a full-scale operating system, like Ubuntu, Windows 10 IoT Core, or Raspbian. Raspberry Pi boards are known to be more powerful than Arduino boards. That’s why they are often used in more complex IoT projects.
• ESP8266 and ESP32. These are two popular low-cost Wi-Fi microcontrollers provided by Espressif Systems that are a good choice for those who build IoT solutions. ESP8266 is an appropriate option for simple IoT projects with restricted budgets, where Wi-Fi connectivity is the primary requirement. ESP32 is often chosen for more sophisticated projects that presuppose the necessity of additional processing power and multiple communication protocols.

Operating systems

• RIOT OS. This open-source operating system was designed specifically for the needs of IoT projects. It is optimized for resource-constrained devices, such as microcontrollers, and supports a wide range of hardware platforms.
• Contiki OS. It is a lightweight operating system that is well-suited for low-power, memory-constrained devices that can be a part of an IoT ecosystem. It is often chosen for embedded systems with limited resources.
• Zephyr Project. This real-time operating system was specifically designed for resource-constrained devices that are often used in the IoT space. This is a secure and scalable OS that supports a wide range of hardware platforms. Today it is used for building for various domains.

Connectivity and networking

• MQTT (Mosquitto). MQTT (Message Queuing Telemetry Transport) is a lightweight messaging protocol that is designed for constrained devices and low-bandwidth and high-latency networks. It is often used in IoT systems to connect devices and transmit data between them. Mosquitto is an open-source MQTT broker. It acts as an intermediary that gets all messages from sensors and devices and routes them to the appropriate receivers. MQTT is preferred in environments where reliable message delivery is critical.
• CoAP (libcoap). CoAP (Constrained Application Protocol) is a specialized web transfer protocol designed for use in constrained devices and networks. It is well-suited for IoT applications where memory and power are limited. libcoap is an open-source C library, which ensures the implementation of CoAP. CoAP is particularly useful for simple, lightweight communications with minimal overhead.
• LwM2M (Wakaama). The LwM2M ((Lightweight M2M) protocol is used for managing IoT devices and enabling service in constrained environments. Wakaama is a C library, which implements the LwM2M protocol.

Data processing and analytics

• Apache Kafka. It is an open-source distributed event streaming platform. Today, it is used by numerous businesses from different industries to build high-performance data pipelines, streamline and facilitate analytics, and ensure the highest performance of mission-critical apps.
• Apache Spark. This multi-language engine is applied for executing data engineering, data science, machine learning, real-time data processing, graph processing, etc, It is known for its speed, ease of use, and ability to handle both structured and unstructured data.
• Node-RED. This flow-based development tool helps users visually program and integrate hardware devices, APIs, and online services. It is used for rapid prototyping and development of IoT apps, automation workflows, and data processing systems.

Development frameworks and libraries

• PlatformIO. It is an open-source ecosystem for IoT development that provides a cross-platform IDE. It offers numerous tools for coding, debugging, and deployment, which helps to streamline the development process. It supports a wide range of microcontrollers and development boards, including Arduino, ESP32, and others.
• Mongoose OS. This IoT firmware development framework supports different low-power, connected microcontrollers such as, for example, ESP32, ESP8266, etc. It supports both Linux-based and embedded systems. This allows developers to deploy solutions across different environments.
• TensorFlow Lite for Microcontrollers. This machine learning library is designed to run ML models on microcontrollers and other devices with a very low memory resource consumption. However, deploying models on microcontrollers requires careful optimization due to limited processing power and memory.

If you have an idea for your own IoT project, you should get a clear vision of how its realization will be organized. When you establish cooperation with a development company, you may find out that the team has its own approach to solving the assigned tasks. Nevertheless, at Cogniteq, we follow a traditional plan for building custom IoT ecosystems. Here are the key steps.

1. Goal definition. First of all, you should identify the problems you want to address or the goals you want to achieve with your system. The set objectives will give you an understanding of the functionality that your solution should have.
2. Choice of the right hardware. Together with your team, you will need to choose the appropriate sensors and devices that will collect data and interact with it.
3. Development of the connectivity framework. It is necessary to opt for the most suitable connectivity type and protocols that will ensure data transmission between devices. Here, the team will also create the required network infrastructure with the chosen open source IoT solutions.
4. Data processing implementation. At this step, it is necessary to establish how data will be collected from devices. Moreover, it is recommended to find a reliable open source IoT database and integrate a cloud platform to store and analyze large volumes of data.
5. User app development. It’s vital to provide users with a convenient mobile or web app to interact with the IoT ecosystem, monitor data, and control devices.
6. Implement security protocols. IoT systems can be rather vulnerable to hacker attacks. That’s why your team should introduce reliable protective measures, such as, for example, encryption and multi-factor authentication (MFA). It is also vital to make sure that your IoT ecosystem complies with relevant industry standards and regulations in your jurisdiction.
7. Testing and validation. In the first turn, your IoT ecosystem should be tested in a controlled environment to identify potential issues and areas for improvement. Your team should pay attention to such parameters as performance, functionality, reliability, and scalability before the deployment. They should fully meet the set requirements.
8. Deployment and monitoring. When your system is fully deployed, it is necessary to continuously track system performance. This helps to detect issues and timely address them.
9. Maintenance. We always recommend our clients schedule maintenance on a regular basis to keep the ecosystem secure and up-to-date.
10. Feedback collection and improvements. You can gather feedback from users to identify pain points and areas for improvement.

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Let’s briefly summarize when it might be advantageous to rely on open-source IoT hardware and software for your ecosystem:

• Limited Budget: If your project has a limited budget, open-source tools can significantly reduce software licensing and development costs.
• Accelerated Development: If you need to speed up the development process, popular open-source solutions can help shorten your time to market. Developers can often find extensive documentation, guides, and other helpful resources that explain how to use these tools to solve various tasks.
• Integration with Diverse Devices: If you plan to integrate your solution with devices and systems from multiple vendors, tools that adhere to open standards are the best choice.
• Control and Autonomy: If you want to maintain control over your ecosystem, open-source IoT devices and tools can help you avoid dependency on a single vendor. This ensures greater autonomy and allows your team to adjust components to meet evolving business needs or switch them as required.
• Long-Term Support and Sustainability: If your project demands long-term support and sustainability, open-source tools can be reliable. These solutions typically have large communities and multiple contributors, which means they are regularly updated and innovated. This reduces the risk of obsolescence compared to scenarios where only a single provider is responsible for the development of a platform or component.

The right choice of tools for building an IoT ecosystem is a very important factor in your project’s success. However, it is also crucial to have a professional development team by your side that will accompany you in your project realization.

At Cogniteq, we work with different types of projects. However, IoT development is one of our focus areas, where we have the richest experience. We deeply understand the peculiarities of modern IoT standards and always do our best to stay aware of all the latest market trends.

Share your ideas with us and we will help you find the best solution.