Cloud computing in IoT: Transforming businesses in 2025

The internet of things (IoT) is reshaping industries by enabling smarter, more connected devices. From manufacturing plants that predict equipment failures to smart cities optimizing traffic flow, IoT applications have become essential for business innovation.

As the number of connected devices grows — expected to exceed 30 billion by 2025 — so does the need for robust infrastructure. This is where cloud computing in IoT plays a critical role, offering scalable, centralized solutions to handle the explosion of data and devices.

What is IoT in cloud computing?

Cloud computing in IoT represents the use of cloud infrastructure to support IoT ecosystems. While IoT devices generate vast amounts of data, cloud platforms store, process, and analyze that data centrally, enabling real-time insights and decision-making. Unlike traditional on-premises systems, cloud solutions eliminate the need for costly physical servers and allow businesses to scale operations effortlessly.

Think of cloud computing as the brain and nervous system of your IoT network. While individual devices collect data and perform specific tasks, the cloud provides centralized data storage and processing, advanced analytics capabilities, and integration between different systems and devices.

For instance, platforms like Viam’s provide an integrated approach, connecting IoT devices to the cloud for seamless data management and analysis.

How cloud computing powers IoT infrastructure

Cloud computing transforms raw IoT data into valuable business intelligence through several key mechanisms:

• Data processing and storage: The cloud offers virtually unlimited capacity to store and process the massive amounts of data generated by IoT devices. This eliminates the need for expensive on-premises infrastructure while ensuring no valuable data is lost.
• Real-time analytics: For business applications that need immediate insights, cloud platforms can analyze IoT data streams in real time, identifying patterns and anomalies that would be impossible to detect manually. This enables predictive maintenance, automated responses to changing conditions, and continuous optimization of operations.
• Remote management: Through cloud platforms, businesses can monitor and manage their IoT devices from anywhere in the world. This includes updating device software, adjusting settings, and troubleshooting issues without requiring physical access.

3 main benefits of cloud computing for IoT

The integration of cloud computing and IoT delivers several key advantages for businesses:

Scalability for growing networks

As your IoT network expands, cloud infrastructure can automatically scale to handle increased data volume and processing needs — ensuring consistent performance no matter the size of the network. There’s no need to guess future requirements or make large upfront investments, since you can grow your infrastructure exactly when you need it.

For example, a global logistics company can monitor thousands of connected sensors using a centralized cloud dashboard without performance lags.

Centralized data management

Cloud platforms provide a single source of truth for all your IoT data, helping streamline operations and maintenance. Tools like Viam’s predictive maintenance solutions leverage cloud analytics to reduce downtime and enhance reliability by identifying issues before they escalate.

Cost-effectiveness

For startups and SMEs, cloud computing makes advanced IoT capabilities accessible without massive infrastructure investments. Pay-as-you-go pricing models mean you only pay for the resources you actually use, making it easier to start small and scale up as needed.

By using solutions like Viam’s data visualization tools, even resource-limited organizations can unlock the potential of IoT.

What is the right balance of cloud vs. edge computing for IoT?

While the cloud is central to many IoT systems, edge computing is emerging as a complementary approach. Edge computing processes data closer to where it’s generated—on the devices themselves—offering low-latency solutions for time-sensitive applications.

Cloud computing excels in data storage, complex analytics, and scalability, while edge computing is ideal for real-time processing and reduced latency. For example, a self-driving car needs immediate edge-based processing to react to road conditions, but its long-term driving data can be stored and analyzed in the cloud.

Businesses often combine cloud and edge computing, with one solution given precedence over another in different scenarios. Let’s look at two examples:

• Remote safety monitoring: In a safety situation where response time is critical, edge solutions are prioritized, avoiding overreliance on cloud connectivity. The data is transmitted and stored in the cloud for ongoing monitoring and analysis.
• Smart home long-term energy usage trends: Cloud systems take the lead here, analyzing large volumes of stored data to identify patterns over time. Edge solutions are in place for real-time smart home applications like lighting and heating.

When to choose cloud vs. edge

In reality, it’s rarely an either-or choice when it comes to cloud and edge. Instead, most successful IoT implementations use a hybrid approach, combining the strengths of both cloud and edge computing:

This hybrid approach provides the flexibility to process data where it makes the most sense while maintaining the benefits of centralized management and analysis.

Business use cases for cloud computing in IoT

Let's explore how different industries are using cloud computing in IoT to transform their operations and drive innovation.

Smart manufacturing and predictive maintenance

Manufacturing facilities use IoT sensors to monitor machinery in real time, detecting anomalies before they lead to breakdowns. By integrating predictive maintenance with cloud platforms, operators can store and analyze historical data to identify patterns and optimize maintenance schedules.

For example, predictive maintenance solutions help manufacturing teams detect potential equipment failures early by analyzing sensor data in the cloud. This proactive approach leads to less unexpected downtime, lower maintenance costs, and extended equipment life span through timely interventions.

Retail: IoT-driven customer insights and inventory management

Retailers use IoT devices to track inventory, analyze customer behavior, and enhance the shopping experience. Applications include:

• Smart shelves track inventory in real-time
• IoT sensors monitor foot traffic patterns
• Connected POS systems provide instant sales analytics
• Environmental sensors optimize store conditions

Cloud-based systems aggregate data from smart shelves and sensors across multiple locations, enabling centralized inventory management and real-time insights into purchasing trends. This allows retailers to anticipate demand and make data-driven decisions about inventory, staffing, and store layouts, in turn reducing waste.

Smart cities: Traffic management and energy efficiency

Smart cities rely on cloud-enabled IoT solutions to enhance public services and visitor experiences. Applications include:

• Traffic management systems that adjust signals in real-time
• Smart lighting that reduces energy consumption
• Connected parking systems that guide drivers to available spots
• Crowd management in sports venues and entertainment facilities

Cloud systems store data for long-term urban planning. Additionally, IoT-connected energy grids can optimize power usage, cutting costs and reducing environmental impact.

Sports and entertainment venues: Crowd safety and enhanced fan engagement

Modern sports and entertainment venues use IoT and cloud platforms to improve operational efficiency, create seamless experiences for fans, and maximize revenue opportunities. These innovations are transforming stadiums and arenas into smart venues capable of handling massive crowds and complex logistics.

Some applications include:

• Crowd management and safety: IoT sensors placed throughout a venue can monitor crowd density, foot traffic, and entry/exit flow in real time, improving patron safety.
• Concessions and merchandise optimization: IoT-connected point-of-sale (POS) systems and inventory sensors in concession stands provide real-time updates on stock levels, while the cloud analyzes the data to adjust future purchases.
• Energy efficiency: IoT systems can monitor and control lighting, heating, cooling, and other utilities; all data is analyzed in the cloud to optimize efficiency.
• Enhanced fan engagement: Mobile apps connected to IoT systems provide real-time information on seating, concessions, and game stats; the cloud manages and processes this data to ensure personalized engagement without overwhelming local infrastructure.

UBS Arena works with Viam to power QuickQueue, an app that allows fans to get a real-time view of the restroom lines in the arena.

Further applications in sports venues include maintenance and facility management and revenue optimization through real-time price adjustments and promotions.

Food and beverage industry innovation

Food processing

In the food processing sector, IoT sensors play a critical role in ensuring product quality and operational efficiency. These devices monitor key environmental factors, such as temperature and humidity, during storage and transportation, ensuring product quality.

By aggregating this data in cloud-based systems, businesses can make real-time adjustments and ensure compliance with safety regulations. Specific applications include:

• Tracking ingredients through the supply chain: Monitor and trace raw materials and produce to ensure safety and regulatory compliance.
• Optimizing equipment performance: Use data to predict maintenance needs and improve the efficiency of machinery.
• Automating quality control processes: Identify defects and maintain consistency in product standards with minimal manual intervention.

By collecting and analyzing data in the cloud, food manufacturers can ensure compliance, reduce waste, and improve product quality.

Quick Service Restaurants (QSRs)

For QSRs, technology focuses on optimizing operations and improving food safety. IoT devices and cloud-based platforms enable better management of various aspects of restaurant operations, including:

• Display optimization: Dynamically update digital menu boards and promotions based on time of day, stock levels, or customer preferences.
• Pantry monitoring: Track inventory in real-time to prevent stockouts or overstocking.
• Refrigeration monitoring: Continuously monitor refrigeration units for temperature fluctuations to safeguard food quality and prevent spoilage.

Discover how Viam is driving innovation in the food and beverage industry—check out our insights and solutions tailored to your needs.

Challenges and solutions for IoT in the cloud

Data security and privacy concerns

One of the main concerns with cloud computing in IoT is data security. With billions of devices generating sensitive data, ensuring its protection is paramount. Viam’s security and compliance features help businesses implement robust encryption and access controls to safeguard their data.

Key security features to look for include:

• End-to-end encryption for all data transmission
• Role-based access control for device management
• Regular security audits and compliance checks
• Secure device authentication and authorization

Latency and connectivity issues

In some IoT applications, even minor delays can have significant consequences. Hybrid models that combine cloud and edge computing address this challenge by processing time-sensitive data at the edge while relying on the cloud for broader analytics and storage.

Explore Viam’s perspective on edge IoT misconceptions to see how these models can reduce latency effectively.

Edge computing solutions help address latency challenges by:

• Processing time-sensitive data locally
• Reducing bandwidth usage through local data filtering
• Enabling offline operation when cloud connectivity is limited

Hybrid architectures that combine edge and cloud processing enable organizations to leverage the benefits of both technologies.

How Viam enables cloud computing in IoT

Viam provides a comprehensive platform that simplifies cloud integration for IoT systems. With its robust architecture and data management tools, Viam empowers businesses to unlock the full potential of cloud computing in IoT. Key features include:

Flexible architecture

Viam’s modular architecture supports diverse IoT applications, allowing businesses to tailor solutions to their needs. Capabilities include:

• Seamless integration between edge and cloud processing
• Secure device-to-cloud communication
• Scalable data processing and storage
• Real-time device monitoring and control

Organized fleet management

With Viam’s All Machines Dashboard, authorized users can remotely monitor their fleet’s performance, gain insights into overall operations, and track the volume of binary and tabular data synced over the past 48 hours.

Efficiently manage large fleets of IoT devices using Viam’s structured cloud hierarchy, which ensures seamless organization and monitoring. Cloud organization hierarchy enables:

• Centralized management of multiple devices
• Granular access control
• Easy deployment of updates
• Group-based configuration management

Advanced data management

Viam’s platform provides advanced data management features, enabling real-time processing and long-term analytics. The data management system provides:

• Automated data collection and synchronization
• Flexible data storage options
• Advanced analytics capabilities
• Easy data access and visualization

Future trends: Cloud computing and IoT in 2025 and beyond

As we look ahead, several key trends are set to shape the integration of cloud computing and IoT, driving business innovation and efficiency.

Increased adoption of AI in IoT-cloud platforms

Artificial Intelligence (AI) is becoming integral to IoT-cloud platforms, enhancing data analysis, decision-making, and automation. In 2025, enterprises are expected to reconstruct their operations with AI at the core, driving significant transformations in productivity and efficiency. Some of these advancements will include:

• Automated anomaly detection and predictive maintenance
• Real-time optimization of device performance
• Natural language interfaces for device control
• Autonomous decision-making capabilities

This shift enables businesses to process and analyze vast amounts of IoT-generated data more effectively, leading to actionable insights and improved operational outcomes.

Emergence of 5G and its impact on cloud-IoT integration

The rollout of 5G networks is set to transform cloud-IoT integration by providing faster data transmission, lower latency, and the capacity to connect a massive number of devices simultaneously.

In 2025, 5G is expected to enable smart cities to become a reality, with everything from traffic lights to household appliances connected and optimized via real-time data streams. Industry leaders are already discussing the development of 6G networks, which they estimate will be available around 2030.

This advancement in mobile network technology will facilitate more responsive and reliable IoT applications, such as real-time safety monitoring and intelligent actuation, enhancing efficiency across various sectors.

Expansion of edge computing

The combination of edge computing and 5G is anticipated to significantly impact the cloud landscape in 2025, enabling faster decision-making and reducing the load on centralized cloud systems. This trend allows for more efficient handling of time-sensitive data, improving the performance of applications like predictive maintenance and real-time analytics.

Getting started with cloud-based IoT

Cloud computing continues to be a critical enabler for IoT innovation, providing the scalability, flexibility, and processing power needed to turn device data into actionable insights. Successful implementations across manufacturing, retail, smart cities, sports venues, and food and beverage industries demonstrate the transformative potential of cloud-IoT integration.

Looking ahead, the combination of AI advancement, 5G connectivity, and hybrid cloud-edge architectures will unlock even more possibilities for businesses to innovate and optimize their operations.

Ready to explore how cloud computing can transform your IoT initiatives? Book a demo to see Viam's cloud-IoT platform in action.