Essential IoT Skills for System Development

by Aug 1, 2023#IoT, #HomePage

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IoT systems are challenging and create complex problems that require specialized IoT skills.

Enterprises without in-house IoT expertise usually opt for a strategic partnership with an established IoT development company with expertise readily available.

Learning and understanding essential IoT skills is critical to starting or scaling existing infrastructures.

Designing and developing IoT systems requires a combination of technical and nontechnical IoT skills as well as knowledge about IoT architecture, hardware design, software development, programming languages, connectivity protocols, security, and more.

IoT consultants work with clients in planning resources focusing on each individual IoT systems’ security, scalability, and efficiency.

Custom Hardware Design and Development

IoT systems require specialized skills in design and engineering and knowledge about hardware components, microcontrollers, electronics and circuit design, PBC layout and routing techniques, power management (battery management, power conversion, and energy harvesting), etc.

IoT skills for hardware design also include signal processing, circuit theory, and board-level design for manufacturing and testing. IoT developers specifically design for manufacturing and testing.

Firmware/Software Development

Customizing hardware also requires understanding embedded systems and having programming skills with languages such as C, C++, Python, and Assembly, for example. In addition, creating IoT systems requires knowledge of microcontroller architectures, platforms, environments, servers, and applications. IoT developers also need knowledge about real-time operating systems, database management, mobile app development, and web development.

Sensors and Actuators

Designing IoT hardware requires knowledge about the characteristics and types of sensors and actuators as well as specific use cases.

IoT development skills with sensors and actuators are essentially about integration techniques to design the interface and control circuits ensuring integration with multiple devices.

IoT developers must understand sensing principles (resistive, capacitive, optical, and inductive sensing) and sensor specifications (accuracy, sensitivity, operating range, resolution, and response time) to choose the appropriate sensor, create sensor networks, and design the signal conditioning and amplification circuits.

Also, knowledge about calibration and testing is needed to ensure accuracy, reliability, and power management techniques for creating designs and functionality that work efficiently with the available power.

Network Engineering and Connectivity Protocols

Creating IoT systems requires knowledge and skills about network architecture, protocols, and standards that enable communication between IoT devices and systems. Network engineering skills include network topologies, routing, switching, and security methods.

Network architecture expertise is needed to design the structure of the physical and logical components of a device’s communication. IoT developers with network skills can also enable integration of devices from different manufacturers.

IoT developers leverage the advantages and limitations of network connectivity protocols to connect devices and gateways with cloud services and transmit data using wireless communication technologies such as Bluetooth, Wi-Fi, Zigbee, cellular, or satellite.

IoT skills in messaging protocols (MQTT, HTTPS, CoAP) are critical, as these establish the rules on how devices communicate and transmit data over the network.

IoT Security

The security of IoT systems is an important architectural component as it protects and secures data transmission and implements encryption, authentication mechanisms, and access control.

IoT developers use safe coding practices that resist vulnerabilities (buffer overflow and injection attacks). They are familiar with SSL/TLS protocols and encryption algorithms in order to conduct vulnerability testing, respond to incidents, and create mitigation strategies (risk management).

Cloud Computing

The cloud is a key component of IoT systems, providing the infrastructure enabling data storage, processing, and analysis. The cloud also provides platforms and services that enable the scalability and flexibility to handle large data volumes.

IoT developers with cloud computing skills understand and leverage the processing power to handle real-time data processing, data analytics, and machine learning models.

IoT Data

IoT devices generate large amounts of data that must be processed to generate insights for business decisions. Therefore, it is fundamental for IoT developers to have data skills and to support data science and data engineering teams to build innovative IoT solutions.

The main data skills required for developing IoT systems are data modeling, database design, schema development, storage technologies (SQL and NoSQL databases), data processing techniques (stream and batch), data visualization and tools, statistical analysis, data mining techniques, and data security.

IoT developers’ skills help to optimize data transmission using data compression and to minimize packet overheads to ensure efficient network usage. In addition, data analysis and visualization help to provide understanding of system performance and optimize data transmission.

Machine Learning/AI

IoT systems are usually combined with machine learning to improve existing products and business processes or solve domain-specific problems using data extracted from IoT devices.

IoT developers learn about the machine learning use case and support from data science, data analysts, and AI engineers and become familiarized with all the data aspects required to build the ML solution.

Machine learning creates prediction services that benefit core IoT systems and must be designed to work with large amounts of data and a specialized data skill set. Data collection, preparation, and exploration methods are performed to build an understanding of the data relationships and attributes for creating a prediction model (ML models).

ML skills are about choosing algorithms, engineering features, training machine learning models, tuning (hyperparameters), monitoring and evaluating the model performance, and supplying many other techniques to support IoT developers with MLOps teams.

Key Takeaway

Developing complex IoT systems requires technical and nontechnical skills, including hardware design, firmware/software development, sensor/actuator integration, network engineering, IoT security, cloud computing, and data analytics/machine learning.

Enterprises without in-house IoT expertise may partner with established IoT development companies to access specialized IoT skills quickly. Investing in planning resources focused on security, scalability, and efficiency is critical to designing and developing successful IoT systems.

With the increasing demand for IoT devices and solutions, acquiring and maintaining essential IoT skills is crucial for businesses to stay competitive.


About Us: Krasamo is a mobile-first digital services and consulting company focused on the Internet-of-Things and Digital Transformation.

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