How to Create IoT Applications: All You Need to Know | Guide

Internet of Things (IoT) technologies are used extensively in every industry around the world. According to the 2024 Statista report, the market is anticipated to grow from $1.06 trillion in 2025 to $1.56 trillion by 2029. However, building IoT systems and keeping them manageable is a difficult task that is often outsourced.

IoT architecture can be incredibly complex because millions of data points flow through multiple networks and platforms. You also need a firm grasp of how to develop IoT applications or devices that match your or your customers' needs. A great deal of decision-making is involved at every stage of production.

In the following sections, you’ll learn what makes IoT important and how it’s used today. We are going to talk about the technologies, standards, and features you should consider for your system or app. At the end, we’ll describe how to create IoT applications and avoid common development challenges.

Where is IoT mostly used?

The Internet of Things is a simple concept that gets confused a lot. To make sure we’re on the same page, IoT is a network of devices and software that communicate remotely.

How does IoT work? These interconnected devices collect and exchange data through sensors, communication protocols, and software. When paired with artificial intelligence and machine learning algorithms, IoT systems can gather information from internet-connected devices, automate processes, and respond to anomalies.

Applications of IoT devices and apps vary across industries. The most common examples are probably in logistics, transportation, and manufacturing. However, current technologies allow for much more sophisticated uses, like remotely controlled energy management and precision farming.

Let’s look at the commonplace use cases that showcase the benefits of IoT.

IoT usage in healthcare:

• Remote patient monitoring devices that track patients’ conditions outside the hospital center, such as blood pressure cuffs, glucometers, and smart wearables (Dexcom).

• Telehealth and telemedicine platforms help doctors provide medical treatment and diagnoses remotely (Philips Virtual Care Management).

• At Overcode, we helped our client develop a Threshold Care App, which enhances senior care through connected devices and real-time data.

IoT usage in agriculture:

• Smart irrigation systems and precision farming via sensors, cameras, and drones (Farmapp, Growlink, and Arable).

• Livestock tracking via RFID tags or GPS collars (Track360 and Chipsafer).

IoT usage in transportation and logistics:

• Real-time fleet management software helps plan and schedule routes, track drivers and vehicles, and automate management operations (Avrios and Fleetio).

• Inventory and warehouse monitoring for product management (Shipcloud and Pickware).

• Cold chain (temperature monitoring) IoT platforms that help preserve high-value products (Inauro and SmartSense).

• Overcode has helped Amber, an electric vehicle warranty startup, develop an IoT app that provides remote diagnostics and warranty plans for electric vehicle owners. The app integrates with Tesla’s software to automatically synchronize data such as battery health and mileage to provide a seamless experience for users.

IoT usage in construction:

• IoT tracking for construction vehicles, equipment, tools, and personnel (itemit and AlignOps).

• Remote control of construction site operations via surveillance cameras, measurement sensors, and AI-enabled tools (Komatsu and Sunbase).

IoT usage in smart homes

• Smart lighting and HVAC that syncs with daily routines and occupancy rates (Philips Hue and Novunex IoT Temperature Control)

• Home security systems with smart locks and motion detectors (TapKey and IEEE Xplore)

• Smart energy metering that facilitates remote appliance control (EasyLink by Eastron Europe)

IoT usage in smart cities:

• Parking lot occupancy monitoring and space optimization (Libelium)

• Smart grids that control power generation, detect system faults, and optimize energy flow (Schneider Electric Global)

• Smart devices that control streetlights and traffic signals (Hackster and SnapLogic)

IoT usage in education:

• Campus monitoring IoT solutions for student flow analysis and personnel tracking (Mapsted)

• Smart whiteboards with interactive displays for collaborative and distant learning (Vibe and SmartTech)

IoT usage in finance:

• Wearable payment devices, such as smartwatches and NFC rings (Apple Watch, Xiaomi, and Ringpay)

• Smart ATMs with biometric authentication systems and built-in cameras (Cash Connect ATM Recycler)

• Sensors that monitor occupancy rates and queue lengths (Freespace)

IoT usage in insurance:

• Telematics (usage-based) insurance that determines premiums by analyzing driving behavior (Move and Earnix)

• Health insurance that rewards consistent data from wearables (Vitality and John Hancock)

IoT usage in manufacturing:

• Collecting data from raw materials, finished goods, and other assets (MESH Asset Tracking)

• Predictive maintenance software that uses temperature, sound, pressure, vibration, and visual data to spot anomalies without human intervention (Siemens Predictive Maintenance)

IoT usage in retail:

• Stock tracking and automated reordering solutions (Baluff)

• Smart self-service vending machines and refrigerators (Neuroshop)

• Customer flow analysis, people counting, and sales data visualization solutions (CountTrack)

IoT solutions are used throughout industries and, when implemented right, enhance efficiency, automate processes, and provide valuable data-driven insights. But to get the most advantages, you should choose the right standards and architecture.

Key IoT standards

IoT communication protocols and standards unify data exchange across the IoT architecture.

These standards define data formats, encryption, connectivity methods, and overhead. So, you need to understand them when building IoT devices and applications.

Short-range protocols

Short-range protocols provide short-distance communication across IoT devices. Examples of these protocols include:

• BLE (Bluetooth Low Energy) allows short-range connections with low power use. It’s common for trackers, smart locks, and other smaller devices.

• WiFi (IEEE 802.11) is widespread for all devices requiring continuous Internet access and higher data throughput.

Long-range protocols

These protocols are designed for wide-area communication. They are ideal for large-scale deployments like agriculture, logistics, and smart cities.

• LoRaWAN (Long Range Wide Area Network) allows gadgets to send small datasets over wide distances. Gateways aggregate signals from multiple nodes and forward them to cloud servers.

Messaging and communication protocols

These protocols enable devices to exchange data efficiently while minimizing bandwidth usage.

• MQTT (Message Queuing Telemetry Transport) uses a publish-subscribe model for low-overhead, bidirectional messaging. Devices connect to a broker to send and receive updates with minimal bandwidth.

• CoAP (Constrained Application Protocol) is a lightweight request-response style similar to HTTP. It’s used in Industrial IoT for machine-to-machine communication that requires extra security (often paired with DTLS encryption).

• XMPP (Extensible Messaging and Presence Protocol) uses XML-based messaging to stream updates via the application layer.

• LWM2M (Lightweight M2M) is used for remote device management in low-power environments, typically for operations like diagnostics and firmware updates.

Security protocols

Security protocols protect the integrity and confidentiality of data exchanged between IoT devices and apps.

• Ascon (NIST) is an IoT encryption standard focusing on low-power cryptographic algorithms.

• Transport Layer Security (TLS) protocols encrypt data transmitted between clients and servers.

• Secure Shell (SSH) provides a secure channel over an unsecured network via a client-server architecture, often employed for secure remote device management.

The right protocols enable secure, real-time data exchange. But a lot depends on your tech stack.

Top IoT technologies

To build a reliable IoT application, a company must choose the right technology stack that depends on the scalability, data processing needs, and security requirements.

The IoT tech stack includes a combination of hardware, software, cloud-based solutions, and communication protocols. Let’s go through the key tech stack:

Integrating devices and sensors into the platforms and analytic tools gives extra visibility and control. That said, you should understand what type of application you want to develop.

Must-have IoT features

IoT applications display data from connected devices first and foremost, but they can do much more than that.

Specific features depend heavily on your application's use case—whether it targets B2B customers, consumer markets (B2C), or industrial IoT environments. Below are some of the IoT features you should consider when planning the development.

• User profile: The profile gathers essential user information and settings. Intuitive profiles improve customer experience. For instance, a fitness app can use profiles to recommend custom workout plans based on individual goals. If your app will be used by organizations or families, consider adding multi-user support.

• Customization: Allow customers to match their IoT app design with their needs. Users may want to configure sensor parameters, define data filtering preferences, adjust automation triggers, and personalize reporting formats. The customization should also include themes, dashboard layouts, quick-access panels, and other visual elements.

• Smart rules: An IoT product could trigger predefined actions based on specific conditions. Examples include workflow adjustments based on demand, delivery rerouting, HVAC reconfigurations based on temperature or occupancy rates, and other features.

• Real-time tracking: Users would want real-time device monitoring via IoT apps. When paired with a logging mechanism, notification modules, and intuitive dashboards, it allows instant quick assessment and emergency responses.

• Security features: An application for IoT should have enough security tools to prevent unauthorized access and protect personally identifiable information. At the very least, you should add multi-factor authentication, tokenized authentications, encrypted communications, and role-based access controls.

• Dashboard: A control center with an overview of connected IoT devices, sensor readings, and key performance indicators (KPIs). It should present relevant data visually, preferably in the form of graphs, charts, and alerts. Technical staff may want to access data logs and generate reports.

• Notifications: Real-time alerts keep you informed about important updates, warnings, or device statuses. You may want to create different types of notifications, like routine updates, automation notifications, and critical warnings that require immediate attention.

• User feedback: Develop IoT applications that allow users to easily contact your support team about issues. It’s best to implement AI-powered chatbots and large language models for low-priority tickets – it saves both customers’ and support teams’ time.

• Onboarding: Add guides and walkthroughs to help the users understand the core features of IoT apps quickly. Contextual hints and demo models can explain the main functions.

• Activity history: A detailed activity history helps both users and support teams diagnose issues and prevent data breaches. The application should log sensor readings, device interactions, authentications (including failed attempts), and reconfiguration.

These must-have features can help you develop IoT web or mobile application.

Mobile app vs web app for IoT: what should you develop?

Mobile and web apps can manage and monitor IoT devices, but these approaches have advantages and limitations.

Mobile app development for IoT

IoT mobile apps integrate with a smartphone or tablet's native capabilities, such as Bluetooth Low Energy (BLE), GPS, and camera access. Mobile apps can store data locally, allowing them to function offline. Smartphone capabilities, like real-time push notifications, are also more intuitive on mobile devices.

This means they’re particularly good for closed-loop systems or operations with limited network connectivity. Think of a fitness band collecting heart-rate data or a smart lock in a home. They’re also useful for IoT solutions in remote sites (like agricultural fields) or critical health applications.

Another factor is the IoT app development costs. For example, mobile apps require separate codebases for iOS and Android, and separate updates need to be pushed through the store review process.

Web app development for IoT

A web app is accessible from any internet-connected device, making it a good fit for IoT solutions. It’s especially compelling for enterprises prioritizing functionality over user experience, as long as web apps offer a scalable and flexible approach to managing IoT systems.

Browser-based IoT application building is easier and less costly compared to mobile app development. Updates and fixes are rolled out on the server side instantly, and there’s no complex store review process. This means any user (with an approved browser) can log in at any time to manage the network.

On the downside, web apps rely on continuous internet connectivity. Unless, of course, you’re developing a progressive web app that uses offline cache for some offline capabilities. Besides, local BLE scanning or native GPS data integration is more limited unless your chosen browser supports the necessary APIs.

A great example of web-based IoT is the Ground Control Coffee Machine App, built from scratch by Overcode for our client. We used React.js, SWR, TypeScript, and Next.js for the frontend, Firestore for database management, and AWS IoT for communication with the coffee machines. To handle IoT device communication even when devices were offline, we employed WS Lambda for data transfer and synchronization,

This Ground Control app offers remote control and monitoring of high-end coffee machines and allows baristas and business owners to fine-tune brewing parameters from anywhere. Read more about the project here.

Comparison table

To help you decide what type of IoT application to develop, here’s a comparison between the key criteria of mobile and web app development.

The choice depends primarily on the business cases. Companies should understand their customer base, their needs, and competing solutions on the market. This, in turn, requires you to plan the IoT development process, starting with extensive research.

How to build IoT applications: 8 stages of the IoT development process

All the knowledge we have shared thus far can guide your choices. The section below further explains how to develop IoT applications and lists key practices and factors you should consider.

Step 1: Define the target audience

Knowing your target audience shapes most of the decisions in development. It will help you choose the most fitting IoT architecture, technologies, policies, and features.

Research uncovers the real needs and pain points of your audience, their individual preferences, and the ways they want to use the app. User needs may directly impact the choice of hardware and communication protocols.

A consumer home IoT app may not need simple control features, while an industrial company may need its devices to connect with an algorithm-based analytics platform. Likewise, an app for senior citizens may need a vastly different UI than software for technical experts.

• Study user demographics, preferences, and tech-savviness. Age groups, professional backgrounds, and technical experience can shape the app’s usability and design choices.

• Interview potential customers. Direct feedback and surveys can reveal what users expect from an IoT product and what other companies lack.

• Identify devices used by them. Consumer-oriented IoT apps are often built for smartphones or smartwatches with BLE connectivity, while enterprise users may use the software from company-approved desktops.

Step 2: Research the market

Market analysis helps make sure that your IoT solution aligns with industry trends and is distinguishable from the competitors. After all, there’s no shortage of applications. According to the NMSC 2024 report, the IoT market size will grow from $99.45 billion in 2023 to $285.63 billion by 2023.

On top of that, you need to learn about all relevant standards, security laws, and privacy regulations.

• Analyze competitor’s offerings. Create a list of the most popular IoT devices & products. Analyze how your direct and indirect competitors solve the same problem with their apps, the features they have, and their business strategies.

• Study software and hardware partners. Look into technical partners and software vendors for IoT devices and applications.

• Observe emerging trends. You need to understand where the IoT is going in your sector. Determine the emerging technologies, user expectations, and other factors that shape the market demand.

Step 3: Select key features and tech stack

Once you understand the market realities and user needs, you need to define core features and technical stack for the IoT app. It’s critical to not go overboard early in the development process and not spread thin on secondary features.

• List essential functionality. Prioritize functionality that solves critical problems to prevent scope creep and costly refactoring. You can add secondary features and integrations after validating your idea.

• Check for compatibility. You should ensure that your IoT devices and apps are compatible with data processing tools, analytical software, and communication protocols.

• Consider an IoT platform. Specialized IoT platforms like AWS IoT and Azure IoT Hub provide tools for device registration, secure data transmissions, and real-time analytics.

Step 4: Create the system architecture

After choosing the tech stack, you should map how the IoT devices and apps interact. This step includes selecting appropriate communication protocols, configuring authentication (security), and configuring data processing.

• Connectivity options. Evaluate each protocol for range, bandwidth, power consumption, and cost-effectiveness. Make sure to incorporate proper secure key management, encryption, and authorization mechanisms.

• Data workflow. Outline how data is collected, stored, and retrieved. Additionally, you should determine whether the data is processed online, on-device, or with a hybrid approach.

• Edge computing. For latency’s sake, consider processing data from the IoT device itself or a nearby gateway rather than sent to the central server.

Step 5: Validate the project idea

You should validate the IoT project idea before committing to resource-intensive full-scale production. Of course, you can skip the validation project and go straight to IoT software development. But, in this case, you risk investing in a product that doesn’t align with user needs or isn’t feasible business-wise.

Additionally, you should validate your architecture under real-world conditions. Stress test and assess data processing to understand if the IoT system works as intended at scale.

• Proof of Concept. PoC helps validate the technical feasibility of a product, allowing you to test the core functionality and connectivity within a limited time and budget.

• Minimum Viable Product. MVP is a more developed but still basic version of the IoT application that you can use to gather feedback from real users.

• Device simulators and pilots. At some point, you can test the prototypes of IoT products and apps in a controlled, real-world environment with a limited group of users.

Step 6: Create a business plan and monetization strategy

Define your product’s core purposes and set measurable goals. Build a roadmap that shows how your software could evolve and grow in a few years.

A sound business plan outlines revenue forecasts, cost structures, and marketing strategies. A key part is to choose your monetization strategy. It goes without saying that it sure is something the customers are willing to pay for the value offered.

The most common options that can be adopted for software for IoT include:

• Per-user pricing (fees for each user of the IoT app)

• Tiered pricing (pricing options with different features, storage spaces, licenses, etc.)

• Pay-as-you-go (charging users only for the compute power and storage they use)

• Freemium model (free version of the base product with advanced features behind a paywall)

• Ads-supported model (basically, a free app with ads with the possibility to upgrade for seamless usage)

Step 7: Choose the IoT development company

The right company can help you build an IoT application faster and with fewer risks. A partner can close skill gaps in your internal team, research your target audience, and choose the optimal IoT technologies.

However, it’s important to hire IoT developers with relevant expertise, necessary tech stack, and industry knowledge. Here are a few tips to help you choose the software development company:

• Study case studies. Confirm that the company has successfully delivered IoT projects, preferably in your industry. See how they solved the client's specific challenges.

• Assess the tech stack. Check whether the company possesses the necessary programming language expertise and the tech stack you need for your IoT product.

• Evaluate the development practices. It helps to know if the company uses Agile methodologies and information security policies. You might want to check the news about the company’s funding and read their blog or LinkedIn posts.

• Review the feedback. Learn what other clients say about the company on review platforms, social media, and other public sources.

Step 8: Build an IoT application

Both app and IoT device development require close coordination between the software, data, and hardware modules (sensors, microcontrollers, gateways) – more so than for other types of products.

Every project is unique and requires different approaches. Our choices depend on a multitude of factors. For example:

• For the frontend, we can use Tailwind CSS to write predefined utility classes directly into the HTML, React and Next.js for dynamic UI building, and Redux for global state management. React Native if you require cross-platform mobile apps for iOS and Android, using the same business logic but a different rendering layer.

• For the backend, our team may utilize GraphQL as a query language for APIs and Prisma ORM for streamlined database interactions. Database management can be done with MongoDB, PostgreSQL, or Supabase.

• For hosting and deployment, we prefer DigitalOcean, CloudFlare, AWS, and Heroku. Meanwhile, we may use Docker and Kubernetes to orchestrate containerized environments.

Continuous testing, security checks, and quality assurance should be done at all stages of the IoT application building. You have to plan software updates or firmware patches (if you also build IoT devices). It requires you to follow post-launch metrics and analyze user feedback.

Each stage of IoT development, provided that you follow them, helps you make a future-proof application that meets strict technical and business requirements.

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Now that we’ve gone through the process, let’s focus on another question: what are the disadvantages of IoT development? More precisely, the challenges and risks.

IoT engineering challenges

Internet of Things development is full of technical, operational, and security challenges. We describe the most important risks below, along with strategies that can help you.

Interoperability gaps

The IoT application building requires you to connect different software modules and devices, such as microcontrollers, sensors, edge gateways, and actuators. These devices and systems can have incompatible data formats or protocols. Additionally, hardware refreshes or replacements can create firmware or driver mismatches.

To avoid problems early on, validate equipment against relevant industry standards (IP ratings, shock/vibration benchmarks, etc.). Choose plug-and-play hardware interfaces so upgrades or replacements won’t require a complete redesign.

Decide early which protocols you want to support and confirm the availability of open APIs or SDKs from hardware vendors. Use cloud platforms like AWS IoT to unify communication across your devices. Additionally, prioritize modular architecture when you build IoT applications – it will ensure that isolated features can be updated without impacting the rest of the system.

Poor connectivity

IoT systems that rely on wireless communication depend on the network quality, which can vary due to environmental factors, geographic coverage, and peak usage times. Service disruption or network outages can disrupt the data stream or lead to safety incidents.

The best option is to deploy multiple network options in places with unstable connectivity (like LTE fallback if the WiFi connection fails). Use low-bandwidth protocols (like LoRaWAN) for remote sensors or short-range BLE for IoT devices in close proximity. You can set some devices to process critical data physically on a local gateway and sync with the cloud once the connectivity is back.

Data management complexity

IoT networks can process thousands or millions of sensors that generate continuous streams of data. The question is whether your infrastructure and analytical systems can handle these high data volumes while maintaining acceptable response times or keeping the cloud costs in check.

Again, you can handle time-sensitive processing on local gateways and send only summarized data to the cloud. For databases, you can use a mix of SQL and NoSQL based on the type of data. The datasets themselves can be divided into smaller segments based on criteria (like location, time range, and device type).

Make sure to use caching to store frequently accessed data in memory. Finally, remember to archive or delete old and low-value information.

Recovery mode risks

A recovery mode can restore default configurations when IoT devices malfunction or require a full network reset. However, poor recovery can corrupt data or leave the device inoperable.

Store a secondary firmware copy and configuration options if the primary firmware gets corrupted. The same goes for the support documentation, device logs, and diagnostic reports – these would help the tech team to recover the functionality.

Security vulnerabilities

Weak encryption, outdated firmware, and default passwords in IoT networks can create entry points for hackers. In some IoT architectures, getting access allows attackers to access private data or even hijack devices.

Security IoT challenges are often overlooked but quite real and dangerous. For example, the 2016 Mirai botnet attack disrupted several online services with Distributed Denial of Service attacks. The entry points for the massive hack were smaller devices, like personal surveillance cameras, routers, and air-quality monitoring systems.

Employ HTTPS/TLS for data in transit and robust encryption (AES-256) for data at rest. For employees and users, make it a requirement to use complex passwords and multi-factor authentication checks. Allow devices to boot only from trusted firmware. Finally, use threat detection and prevention systems that use AI-driven analysis – something that can spot anomalies and isolate potentially affected IoT endpoints.

Regulatory and data privacy issues

IoT infrastructure has to follow relevant data privacy regulations that dictate how you should process, store, and share data (personally identifiable information). These laws can vary based on your company’s location and user base and often include the General Data Protection Regulation (GDPR), UK-GDPR, Health Insurance Portability and Accountability Act (HIPAA), and California Consumer Privacy Act (CCPA).

Failure to protect user data sufficiently or non-compliance with general procedures can result in lawsuits, criminal charges, and heavy fines. That’s not even mentioning brand image and customer loyalty.

Integrate data anonymization tools, encrypted communication, and strict security checks from the start of the IoT product development. Restrict database queries to authorized roles and log every data interaction. If laws require data residency, you should store it in region-specific data centers. It goes without saying, but make sure you’re sending all the necessary private notices and user consent forms for data sharing.

Quality assurance problems

Quality assurance is complicated because of how unpredictable the IoT architecture can get. You have to test the application’s code, the device’s firmware, network connectivity, cloud services, and databases.

Without proper experience, you can overlook many problems caused by unexpected usage or real-world conditions. For example, inconsistent firmware can potentially break the device, and unstable temperature can impact network latency. Some problems can be unclear without proper review – IoT systems can appear to be working as normal but show inaccurate information.

The only way out is to collaborate with hardware manufacturers, firmware developers, and cloud engineers. You also need experienced developers, testers, and QA specialists who can conduct on-site or real-device testing under various conditions.

That’s why you should consider partnering with a professional team to help you develop IoT applications.

Why Choose Overcode for IoT App Development?

Building an IoT application requires knowing the target audience, picking the right technical stack and standards, and validating the product through PoCs or MVPs. That’s just the beginning, though. You need to constantly iterate and update the apps, maintain the network, and ensure data security.

You need a deep understanding of IoT architecture and the specific challenges of development in this niche. That’s why you may need help from an experienced team.

At Overcode, we transform complex ideas into practical products or enhance existing software. Our team can assist you at every stage, from picking hardware and communication methods to setting up data flows and programming the application layer.

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