How to Build an IoT Application: The Way to Success

In the era of digitization, many aspects of people’s lives are being significantly improved by remotely controllable devices & whole infrastructures — the so-called Internet of Things.

This industry is continually growing & bringing new products: a nearly $250B market is starting to surge and is projected to have grown by no less than 5 times by 2027.

 
 

✅ Top Things to Pay Attention to When Developing a Software for Your IoT Device

The process of IoT app development, including companion app development, can be quite challenging in terms of technological nuances. Yet, to avoid potential pitfalls and make the process to create an IoT app smoother and easier, we recommend paying attention to a few specifics. Here they are!

 

Firmware

Firmware is a software program that’s “responsible” for communication between hardware systems:

• Hardware Boards.
• Edge Computing.
• Sensors.

It can be developed using different languages from C to Python. We at Stormotion work with multiple programming languages such as React, React Native, Java/Kotlin, etc.

So, depending on your use case, a certain language might suit your needs better. For instance, with React Native, you can get both mobile and web apps by using the same code, which isn’t the case for C.

If you need any help with the development or want to decide which language can be more suitable for your use case, feel free to reach out to us!

What we’d like to draw your attention to here is firmware updating. Nowadays, the easiest way for an IoT app developer to implement this is with Over-the-Air (OTA) updates, meaning that the new version is simply installed remotely.

It’s important when you make an IoT app since sometimes it is prohibited for users to stick to older versions of firmware, which, basically, blocks access to the thing until it’s updated.

Imagine if somebody isn't able to open the door because of an outdated version of the firmware when being late for a flight. That can damage the brand’s reputation and cause a loss of trust.

So, first and foremost, think about making it optional or warn about the forthcoming update several times in advance. Besides, it might be a good idea to offer users to schedule it by themselves.

 

Third-Party Integrations

If your use case implies integration of third-party devices, you should pay attention to these aspects of Internet of Things application development:

• Data Acquisition Module.
• Data Processing Module.
• Communications Module.

Let’s review them one by one, a task often undertaken by an internet of things app developer.

 

# 1: Data Acquisition Module

In building an IoT application, the Data Acquisition Module plays a vital role as the part of the hardware that helps to receive physical signals and convert them into digital signals for processing.

The physical signals here, captured by IoT sensors, imply:

• Temperature.
• Vibration.
• Motion.
• Light & others.

When working with this part, there are several aspects that we’d recommend taking into account:

• Signals that will be measured. It’s essential to decide what sensors and devices for measurement you’ll need.
• The number of sensors.
• The speed needed for the measurement of physical signals — indicators such as sample rate.
• The needed measurement accuracy — indicators such as sensor resolution.

Once you have answers to these questions, you’ll be able to determine the requirements for this module (in particular, your use case).

 

# 2: Data Processing Module

This part of devices serves several goals:

• Data processing.
• Analytics.
• Data storing & other computing operations.

Your role here is to understand & explain the end goal of the development of the Internet of Things so you can guide your development and engineering teams.

Here, the key points might be:

• The amount of data that’ll be processed. This indicator will depend on the number of sensors, whether you’ll need real-time control and analytics, how much space you’ll want to leave for future updates, any size constraints, etc.
• The amount of data you’ll need to store locally. So, the data you’ll obtain will be either sent to the Cloud (or any external storage) or stored locally. Thus, you’ll need to decide how much data you’ll need to store temporarily to do all the necessary calculations or for buffering purposes in case your cloud connection crashes. Besides, don’t forget to consider whether or not you’ll need your “thing” to work offline, and if yes, for how long as that will define the capacity of the local storage.

At first, it may not seem that significant but eventually, these two indicators will have quite a big impact on your development costs, size of the “thing,” number & complexity of features, etc.

 

# 3: Communications Module

This part of the hardware is intended to enable communication between your external storage and any third-party integrations/devices.

It can be set up by using communication ports such as USBs and wireless protocols (we’ll talk about that in the next subsection).

Your device can be either integrated with other parts of the hardware or be a separate device. The second option is called the gateway architecture and it might be more cost-efficient since you can only place one gateway for an area that will collect data from all sensors and send it to the storage.

 

#4: Testing with real devices or prototypes

In the process of building an IoT application, testing with real devices or IoT prototypes isn't just a step in the development process. It's a rigorous validation of your IoT ecosystem's readiness for the real world. This phase is where the digital meets the physical, and your concepts are put to the test — literally. What IoT application developers need to pay attention to:

1. Device Robustness: Devices should be tested for their functionality, durability, and response under various environmental conditions. This includes stress testing and scenario-based testing to simulate real-world use cases.

2. Network Reliability: Network testing is crucial, especially for devices that will be deployed across diverse locations. This ensures consistent connectivity and performance, regardless of the network conditions.

3. Application Interaction: The application layer requires thorough testing to ensure seamless interaction with the IoT devices. This includes testing the user interface, data processing capabilities, and integration with other systems.

4. Security Assurance: Security testing is paramount. Conduct vulnerability assessments and penetration tests to uncover any potential security issues that could compromise the integrity of the IoT ecosystem.

 

🤔 How to Choose the Right IoT Connectivity Option?

When developing software for your IoT device, it is essential to enable data exchange among various layers and components of the infrastructure, including 'things,' gateways, sensors, servers, and end-user solutions.

This communication is possible because of the so-called IoT protocols which can be considered as the language that machines use for data transmission.

There are quite a few of them, so when choosing one protocol for your IoT solution, there are a number of factors that should be taken into account. For instance, bandwidth, connectivity range, power consumption, price, industry, and many others.

For you to better understand what all these protocols are about, we’ve decided to make a table with the main characteristics of each protocol:

In case it is ready, the only thing at this stage of the development that can slow down the process is bugs that can normally be solved fairly quickly.

However, If the firmware is at the early stages of development, the process can become markedly slower because it might be complicated to control the Internet of Things development processes (application and firmware), test them, fix bugs, etc. all at the same time.

So, we highly recommend you to consider looking for devices with already developed and tested firmware before you start the Internet of Things app development.

 

# 2: Security

One of the major problems of the IoT industry, particularly in sensitive sectors like IoT in healthcare, which includes the development of apps to track mental health, is security since there are not enough standards that developers/engineers would have to follow to make the system 100% reliable.

Besides, the number of devices such as sensors is high in most IoT solutions which makes them more vulnerable and easier for hackers to spot a breach in.

To increase security, think about doing the following:

• “Security by design.” It’s a system that allows to prevent rather than fix any breaches in an IoT security system with the help of regular testing, authentication safeguards and the best cybersecurity practices.
• Regular updates. Through trial and error, you can figure out the best ways to make the device as secure as possible, so we recommend making updates as soon as you have something to improve in your security system.
• Use great security protocols such as HTTPS and TLS (transport layer security).

• Multi-factor authentication. It can include biometric authentication (fingerprinting, face and voice scanning, etc.), end-to-end encryption (full encryption which implies that only the sender and the recipient can read whatever it is), personal questions, email/phone number confirmation, complex password that’s changed every once in a while, etc.

 

# 3: Inconsistency

If your app is intended to allow users to control several devices within one app, you might face the problem of your app being inconsistent with certain devices from other brands.

For example, if a user buys your smart toaster but then opts for a fridge from another company, you can’t guarantee that they’ll be able to control both of these devices in your app which can damage your services’ quality and reputation.

All of that is because the standardization isn’t unified, and all companies use different APIs, protocols, and security features.

The most tricky part is that you can’t really do anything about it; a possible solution might be to allow integrating third-party services through their APIs, but that will depend on your specific use case.

 

# 4: Recovery Mode

It might be a good idea to add a so-called “recovery mode” into your IoT application in case users need to restore lost data from a cloud or another storage.

This feature is something that should be implemented before developing an app since to implement it you need to allow access to the device's bootloader which is a lot easier to do when manufacturing the “thing” itself.

 

# 5: Quality Assurance

Each & every update of the IoT firmware, especially when you build a smart home app, should be tested to check how it affects the application (processes like fixing bugs, testing the app’s behavior, checking if a cloud or another storage is synchronized well enough with the system, etc.).

However, the most important part to keep in mind here is that such quality tests can’t be performed well enough as simulations meaning that your development team might need to run them manually or with real devices (if possible) so that your services are as “seamless” as possible.

 

# 6: Issues and disruptions while connecting software and devices.

When developing Internet of Things (IoT) applications, a task often facilitated by mobile app development services, connecting software and devices presents a unique set of challenges. Here are some critical issues and disruptions that developers and users may face:

1. Hardware Compatibility

Choosing the right hardware goes beyond basic compatibility; it involves ensuring that the devices can operate under specific environmental conditions and can be easily updated or replaced as technology evolves. For instance, sensors used in outdoor applications must be robust enough to handle weather variations.

2. Network Reliability

The choice of network protocol can also impact the energy efficiency of IoT devices. For example, protocols like Zigbee or Z-Wave are often preferred in smart home applications due to their IoT low power consumption and mesh networking capabilities, which provide greater coverage and reliability.

3. Data Management

For internet of things application developers, effective data management also includes the ability to process and analyze data at the edge of the network. This edge computing approach can minimize latency and bandwidth use, leading to more responsive IoT applications.

4. Security Threats

Security measures must be proactive and include end-to-end encryption, regular firmware updates, and secure boot processes. The integration of AI and machine learning can also play a role in detecting and responding to security threats in real-time.

5. Scalability Concerns

Scalability is not just a technical challenge but also a business consideration. As the number of devices grows, the cost implications of data storage and processing become significant. Planning for scalability must include a cost-effective strategy for data management.

6. Technological Inconsistency

To address inconsistencies, developers are encouraged to use standardized APIs and protocols that ensure different devices and systems can communicate effectively. Adopting industry standards can also facilitate easier integration and interoperability.

7. Software Complexity

The complexity of IoT software is often managed through modular design, allowing different functionalities to be developed and tested independently. This approach can also make it easier to update and maintain the software over time.

8. Cloud Dependencies

The strategy of diversifying cloud services in IoT projects points to the broader skill set required, including how to develop IoT applications that are versatile in cloud environments. Moreover, using local processing for critical operations can ensure functionality even when cloud services are unavailable.

9. Interoperability Issues

Standards like MQTT and CoAP are designed to enable interoperability in IoT. Adopting such standards can help ensure that different devices and systems can work together seamlessly, regardless of the manufacturer.

10. Regulatory Compliance

Compliance is not static; as technology and regulations evolve, IoT systems must adapt. This means implementing a compliance strategy that can accommodate changes over time, such as the introduction of new privacy laws or industry-specific regulations.

Let’s take a closer look at what services an IoT platform can provide:

1. Hardware connection, e. g., between a “thing” & sensors.
2. Implementing and managing protocols.
3. Adding authentication and security features.
4. Analyzing, gathering and providing infographics of the data from “things.”
5. Connecting current systems with different parts of the hardware.

To navigate you through the market of IoT platforms, we’ve decided to make a list of the most widely-used & trustworthy platform providers with a variety of services. Here you go:

• IBM Watson.
• Azure IoT (from Microsoft).
• Google Cloud IoT.
• AWS IoT (from Amazon).
• Salesforce IoT.
• Zetta.
• Kaa.
• Arduino IoT Cloud.
• Carriots (or Altair).

In fact, there’s no specific case when we could tell you that you should most likely use an IoT platform or a specific type of it (like a cloud-based one) since it really depends on your personal preference.

Thus, by using such a platform, you can speed up the development process and reduce the up-front costs. However, in the long run, it might be less beneficial since the fees are usually subscription- or use-based which means they can increase in the future.

So, your data collection strategy can depend and be based on the following factors:

1. Frequency & Accuracy. Basically, this way, you correlate the desired accuracy of the data with the frequency of collection needed to reach it. It can happen that a certain level of accuracy will be sufficient and thus a higher level will not be providing any additional value. So, you will be able to reduce the measurement frequency which will save you resources used for data collection while still allowing option accuracy level.
2. Time. In case there’s a specific period of time after which the data won’t be considered fresh and relevant anymore, you can set a “maximum time gap” between the last and the next measurement. This way, your data collection will be performed with an interval fully tailored to your use case.
3. Energy. In fact, this one is similar to the frequency example. However, here, the key factor is energy consumption, meaning that a certain accuracy & amount of data is sufficient and the energy consumption can be minimized to as little as it’s enough to reach the goal.
4. Privacy. If you need to only measure a certain amount of data without going any deeper even by accident, you can add the so-called “noise” to the measurement process. It’ll interfere with the process once the needed level of data accuracy is reached, allowing you to still be compliant with all the necessary regulations & respect privacy.

 

# 2: Data Processing 🔄

Data processing is quite demanding in terms of resources, meaning that you should be attentive when deciding what to process and what not to process.

First and foremost, you should pay attention to how much data you need to analyze to keep your system functioning. After that, try to limit it to this amount of data so the process is cost-, energy-, and time-efficient. Besides, you’ll need additional tools for handling the data which will of course create additional costs.

If you use third-party processing solutions, make sure to properly look into their statistics and your service agreement (which is often neglected). Something you might want to look for is how often the system is exposed to breaches, what the terms of changing the vendor are, etc.

Additionally, it might be a good idea to allow real-time data processing since it can be essential for industries such as agriculture, healthcare, weather forecasting, or even smart door locks.

 

3: Data Storage 📚

Normally, IoT devices don’t have much storage which makes it essential for most use cases to use external storage.

So when picking storage, you should pay attention to its ability to quickly retrieve the data for any needs. Besides, it might be a good idea to use one that allows searching data by timestamps and other filters so you can easily find what you need.

Furthermore, it may be smart to make the data exportable and moveable to various formats to see the different highlights for comparison & analysis.

 

# 4: Data Analytics 📊

Data analytics is a crucial activity that IoT solutions perform to be able to function & provide value for end-users. Its core function is to separate the chunks of data that come in every day while “things” are functioning and extract the necessary information from it so it can be transferred to a user.

Basically, this process has to be gone through before actually visualizing it for customers so that instead of having to look at raw data they’ll be able to look at something valuable to track dynamics, have clear conclusions, and make data-driven decisions.

It’s essential to offer real-time data analysis so users can take immediate action when needed (depending on each specific use case). Additionally, data analytics can:

• Be performed over a given period of time so users can observe the general tendency and trends.
• Offer conclusions and steps needed to be taken based on the analysis.
• Help make marketing campaigns more personalized and targeted, etc.

 

# 5: Data Visualization 📈

To present the analyzed data to end-users, you’ll need certain tools for visualization. Most often, this function implies:

• The visualization itself (Real-time table, sensor overview, charts & tables, etc.).
• History so users can access previous data visuals.
• Notifications to make sure that users know when something new comes up.
• Alerts — something that requires immediate attention and/or action.

We’d like to pay special attention to alerts. Here, it’s of high importance to develop the habit of instantly paying attention to urgent situations and reacting accordingly; you can definitely help your users with that.

Think about adding special sound effects when alerts come up or marking them with a flashy icon so they stand out among all the other ones.

Also, it might be a good idea to categorize the visualized data. To be more specific, don’t offer too many graphs that represent the same data with different variables. Instead, consider making it manageable for users to choose what variable is presented for them.

Take smart sprinkles as an example. Instead of showing humidity on each field with a separate chart, add a tab where users can choose what field they want to be presented.

 

# 6: Device Management 💻

You’ll most likely need to add different features for users to control the “thing” along with its components. That may include:

• Provisioning (adding a device to the system) and Authentication.
• Configuration and Control (turn on/off, change modes, etc.). It’s important to take even more control of the device’s components (like frequency of data measurements, data transferring to the cloud, etc.).
• Monitoring and Diagnostics. This feature is intended to display all processes, warn if something is off, and regularly diagnose to see if there are any breakdowns.
• Software Maintenance and Updates. This can help you & your users fix everything remotely (if possible).

Additionally, you can implement a feature for grouping parts of the device like sensors. It might be a good idea to add a hierarchy of groups. For instance, sensors are located in one device, and devices are grouped as a fleet.

Also, think about adding an extended searching feature to your device management functionality. It can include searching by:

• Device ID.
• Device state (on/off, working/broken, etc.).
• Device type (if you have several) & others.

This searching feature is more suitable for broader “things,” e.g., for hospitals, however, it’s applicable to devices of any type & scale. It all depends on your use case.

Naturally, each assistant’s developer and provider that makes their device integrable offers an API just for this purpose. Any voice-controlled command is enabled by “skills” and “action” in Amazon Alexa and Google Home respectively. These commands need to be implemented into a server which will then “perform” them as it’s required for integration.

For Google Home, you can use any server but Alexa’s “skills” must be executed on the AWS Lambda server.

After this step is done, you’ll need to ensure security & privacy policy compliance, which is also partially dictated by providers. For “skills” and “actions” to actually work, you and/or your development team need to send them to providers for approval. The process might take up to a week.

Surely, there are many ready-to-use commands that are already available, so it might be a good idea to educate yourself on them. In case you find that everything you need is already there, you’ll be able to skip this step.

 
 

📋 12 Steps to Create IoT Applications

The development of IoT applications is a complex process that involves several steps and considerations.
 

🎯Step 1: Define Your Objective and Scope

Before diving into the technicalities, it's crucial to define what you want your IoT application to achieve. Whether it's smart home automation, healthcare monitoring, or industrial asset tracking, having a clear goal will guide your development process. Each sector presents its own set of challenges and opportunities, and understanding these can significantly influence the direction and success of your IoT solution.
 

🔩Step 2: Choose the Right Hardware

IoT devices vary from simple sensors to complex industrial machines. Select hardware that is energy-efficient, has the necessary sensors, and supports wireless communication. The choice of hardware will significantly influence your application's capabilities.

Platforms like Arduino for prototyping and Raspberry Pi for more complex tasks can be excellent starting points. For industrial-grade hardware, Siemens IoT offers robust options. You can read more about how to choose hardware a little higher in the article.
 

🔒Step 3: Establish Secure Data Collection

Data is at the heart of IoT. Ensure that your application can collect data securely by implementing robust encryption and protecting the integrity of the device settings. This step is crucial to prevent data breaches and ensure user trust.

Utilize platforms like Telit, which offers modules, platforms, and services for secure data collection, ensuring end-to-end IoT security.
 

🌐Step 4: Organize High-Performance Data Streaming

IoT devices can generate massive amounts of data. Your application must be able to handle this data efficiently. This could involve using non-traditional data streaming mechanisms that are optimized for IoT workloads.
 

☁️Step 5: Create a Centralized Data Storage Solution

Most IoT applications require a centralized system for data storage and analysis. Cloud solutions are often ideal for this purpose, providing scalable and efficient data handling capabilities.

Amazon Web Services (AWS) provides scalable cloud storage solutions like Amazon S3 and DynamoDB, which are ideal for handling large IoT datasets.
 

⚙️Step 6: Develop a Scalable Backend

The server-side of your IoT application, especially in BMS software development, should be able to sort, process, and analyze the data. Utilize IoT development platforms that offer extensive functionality for creating a scalable and intelligent backend. If you're building an app for electric vehicle users, factoring in the cost of developing PlugShare like app will help estimate the backend infrastructure costs.

Microsoft Azure IoT Suite or Google Cloud IoT offer powerful backend services that can scale as your application grows.
 

🖌️Step 7: Design an Intuitive Front-End

The user interface of your IoT application should be user-friendly and provide valuable insights from the processed data. Modern IoT platforms allow developers to create sophisticated front-ends that enhance user experience.
 

🛠️Step 8: Utilize IoT Development Platforms

Several platforms can accelerate IoT app development. Some of the popular ones include:

Azure IoT Suite: Offers a comprehensive set of tools for integrating devices and managing data.
Amazon Web Services (AWS): Provides a robust infrastructure with enhanced security and flexibility.
IBM Watson: Supports AI-driven analysis and secure device-server communication.
Oracle IoT: Known for its cloud solutions and a wide range of features for IoT development.
KAA IoT: An open-source platform that offers a rich toolkit for IoT app development.
 

🚀Step 9: Consider the Fastest-Growing IoT Areas

When developing your application, consider focusing on rapidly growing IoT areas such as smart homes, retail, healthcare, logistics, and manufacturing. These sectors are ripe with opportunities for innovative IoT solutions.
 

🔬Step 10: Test and Iterate

After developing your IoT application, thorough testing is essential. This includes testing for functionality, security, and user experience. Based on feedback, iterate and improve your application.

For testing, use platforms like Mocha for JavaScript applications, and for device simulation, the Azure IoT Device Simulation tool can be very useful.
 

📦Step 11: Deployment and Maintenance

Deploy your application and ensure that you have a plan for ongoing maintenance. This includes updating the software, managing the devices, and continuously improving the application based on user feedback.

Docker and Kubernetes can help in deploying and maintaining your IoT applications, providing containerization and orchestration services.
 

📈Step 12: Scale Your Solution

As your IoT application gains traction, attracting more users and generating larger volumes of data, the need to scale your solution becomes imperative. This scaling process may encompass a spectrum of enhancements and upgrades.

Google Cloud's Bigtable offer robust and scalable solutions that can grow with your user base.

That includes:

1. Number & complexity of features.
2. Scope of the device.
3. Chosen technology.
4. Costs of third-party services (if needed).
5. Your developers’ hourly rate.

Generally, development costs might range from $22,000 to $70,000:

The Norsk Guardian app is designed to preemptively alert users to potential battery issues, preventing critical situations at sea. It provides real-time monitoring of battery temperature, voltage, and charge, among other parameters.

For SportPlus, we created a companion workout app that connects with their fitness devices. This project presented a unique challenge as we discovered the need to accommodate four different BLE protocols due to the inconsistency in the operation of the workout machines. To address this, we developed a generic protocol handler with BLE integration that ensured stable communication between the app and all the devices.

Additionally, we implemented a CMS system that allows the SportPlus team to manage and update workout content, providing added value to the users.