Enterprise IoT – Benefits, Use Cases, and Real Examples

Sudeep Srivastava February 28, 2024
Enterprise IoT

Operational inefficiency, lack of real-time data, security vulnerabilities, and high energy costs represent critical challenges encountered by enterprises in the current business landscape. These issues highlight the pressing necessity for innovative solutions that can revolutionize operational frameworks, elevate decision-making processes, and ensure sustainable development in today’s rapidly advancing digital age.

Enterprise IoT (EoT) emerges as a pivotal player in this transformation, presenting unparalleled prospects for organizations across diverse sectors to leverage the capabilities of interconnected devices.

According to a Grand View Research Report, the global enterprise IoT market was valued at $ 574.2 million in 2023 and is expected to reach $1.42 billion in 2030, witnessing a CAGR of 14.1% from 2024 to 2030. The increasing market share can be attributed to the increasing adoption and value attributed to IoT technologies in the enterprise sector.

Global Enterprise IoT Market Size

In this comprehensive guide, we’ll explore the immense value of enterprise IoT, provide detailed real-world examples, and break down the key steps for building a successful large-scale IoT strategy.

Collaborate with us to future-proof your business with Enterprise IoT

What is Enterprise IoT?

The Enterprise Internet of Things refers to the widespread use of connected sensors, devices, equipment, and assets across large organizations to generate data for optimizing operations. By embedding internet-enabled sensors and connectivity in machinery, vehicles, equipment, and other assets, organizations can collect and analyze real-time insights on performance, usage patterns, remote monitoring, location tracking, and more.

Unlike consumer IoT, which focuses on smart homes and wearables, the Enterprise of Things (EoT) targets commercial and industrial applications at scale. Leading organizations use business IoT to boost efficiency and safety. However, deploying enterprise Internet of Things requires robust data analytics platforms, stringent security measures, seamless integration with legacy IT systems, and specialized development expertise.

More on enterprise IoT development later, let us now first explore the multitude of benefits it brings to businesses.

Benefits of IoT in Enterprises

Implementing business IoT solutions delivers quantifiable financial and operational benefits directly impacting the industry’s bottom line. Let us look at some of the major benefits of Enterprise IoT platforms in detail below.

Various Advantages of Developing Enterprise IoT Solutions

Increased Operational Efficiency

Businesses can precisely monitor performance and usage patterns by outfitting machinery, vehicles, and equipment with IoT sensors. This generates data to optimize processes and reduce downtime. Instead of scheduled preventive maintenance, sensors can detect emerging issues early and alert managers before failures occur.

This enables just-in-time maintenance when replacement is needed rather than routine upkeep. Continuously monitoring equipment conditions lets organizations move from reactive to predictive maintenance schedules. All of this boosts efficiency and productivity.

Enhanced Safety and Regulatory Compliance

Facility sensors provide continuous visibility into safety practices, hazardous situations, and environmental conditions. Managers gain insights to correct unsafe circumstances proactively before accidents or emergencies occur. IoT data facilitates compliance with regulations by detecting problems early.

Substantial Cost Savings

Enterprise IoT solutions yield major cost savings from increased labor and operational efficiencies, energy savings from usage reductions, decreased downtime and waste, lowered inventory carrying costs due to just-in-time ordering, and other benefits.

New Revenue Opportunities

Monetizing IoT data represents a game-changer for incrementally boosting revenues. Organizations can develop new usage-based or subscription service business models with real-time equipment insights. IoT for businesses also increases sales touchpoints with customers to sell additional services.

Sustainable Competitive Edge

IoT for businesses provides information from data that other competitors do not have­. It allows businesses to stand out with bette­r products, personalization, and predicting what will happen. The­ improvements in how things work unlocked by IoT make­ it a must to stay competitive in the digital world.

Common Enterprise IoT Use Cases

Enterprise IoT is reshaping the business landscape, driving innovation and operational efficiency across a wide range of industries. From streamlining supply chain logistics to connected healthcare, the applications of IoT in the enterprise are unlimited. Here are some of the most common use cases of Enterprise of Things to understand how businesses are leveraging this technology.

Multiple Use Cases of Enterprise IoT

Smart Manufacturing

Industrial IoT connects production equipment to enable predictive maintenance before failures occur. Sensors also track equipment performance metrics like pressure, vibration, and temperature to optimize processes, including energy consumption, and automate tasks where possible. Companies like Siemens, GE, and Bosch are using IoT on factory floors to improve quality control, increase output, and shorten production cycles.

Connected Logistics

Fleet tracking telematics analyzes real-time vehicle location, driver behavior, fuel usage, cold chain integrity, and cargo conditions to optimize routing, loading, and delivery times. IoT enables automated inventory management through smart warehousing with sensors tracking stock levels and expiration dates in real-time. Logistics firms like UPS, FedEx, and Maersk are applying IoT to coordinate planes, ships, and trucks for faster and more efficient transport.

Automotive

IoT in the automotive industry is fundamentally transforming various aspects of vehicle functionality, safety, and the overall driving experience. Through the integration of sensors and networks in connected cars, real-time data exchange between vehicles and their surroundings is made possible, facilitating significant progress in autonomous driving capabilities and predictive maintenance practices.

How we developed an IoT-powered intuitive gesture-recognition app

Smart Facilities

Modern offices, campuses, and commercial buildings are outfitted with integrated IoT sensors for HVAC, lighting, occupancy detection, indoor air quality, leak detection, asset tracking, and security monitoring. These systems are coordinated by building management platforms to optimize energy efficiency, space utilization, and maintenance based on granular room-level insights. The Edge building in Amsterdam has over 30,000 sensors to automate lighting, heating, and more based on precise usage patterns.

[Also Read: Smart Homes – IoT in Real Estate Leading the Future]

Utilities and Energy

Smart electric, oil and gas, and water meters communicate consumption data automatically while detecting anomalies and outages. Renewable energy assets have embedded sensors to monitor performance, predict maintenance needs, and forecast power production. Utilities like Duke Energy, Enel, and Woodside use IoT to reduce leaks, avoid outages, and optimize assets.

FinTech

IoT in the Fintech sector enhances the provision of personalized, secure, and efficient financial services. Through the integration of IoT devices with financial platforms, banks and financial institutions can access extensive customer data, facilitating customized financial recommendations, identification of fraudulent activities via monitoring of unusual behaviors, and the facilitation of seamless payment processes. This helps in reshaping how individuals and businesses engage with their financial affairs, making transactions more user-friendly and safe.

Connected Healthcare

Hospitals implement IoT solutions to track medical assets, monitor diagnostic lab equipment, adjust HVAC in patient rooms, and integrate electronic medical records. Patient wearables collect real-time health metrics, including heart rate and glucose levels, to inform diagnoses and treatments. Health systems like Mayo Clinic and Kaiser Permanente use IoT data to improve patient experience, safety, care coordination, and outcomes.

Smart Retail

Retail IoT use cases include automated checkout, in-store analytics to study traffic patterns and shopping behavior, targeted promotions based on purchase history, optimizing inventory levels, and loss prevention. Companies like Walmart and Amazon implement camera systems and sensors to enable grab-and-go shopping without checkout lines. Digital signage displays personalized promotions as shoppers browse.

Connected Products

Manufacturers across industries are building IoT connectivity and data collection capabilities into products to generate usage insights for design improvements and provide additional digital services. Tesla vehicles have integrated sensors that feed performance data back to the company while also monitoring part failures and maintenance needs.

Smart Agriculture

Precision farming leverages IoT to monitor crop growth, soil conditions, equipment status, and livestock health in real time. Farmers use IoT data to reduce waste, optimize inputs, improve yields, and automate irrigation and harvesting.

Aviation

IoT in aviation helps in taking flight operations, maintenance, and passenger experiences to all new heights. By embedding sensors throughout aircraft, airlines and airports can monitor everything from engine performance to baggage handling in real time. This leads to enhanced operational efficiency, reduced downtime, and improved passenger experiences.

Challenges Enterprises Face in IoT Implementation

While the business potential of enterprise Internet of Things is immense, it also poses distinct technological and organizational challenges that must be addressed thoughtfully. Let us look at them in detail below.

Multiple Challenges of Enterprise IoT Implementation

IoT Data Management

The massive flow of real-time data in different formats from hundreds or thousands of IoT sensors and systems makes collection, normalization, and analysis complex. Data science expertise is essential to develop systems capable of aggregating vast, streaming data sets and extracting meaningful insights through analytics. Lacking robust data management capabilities will overwhelm organizations with a flood of IoT data with minimal value.

Implementing advanced data management platforms that automatically normalize and analyze incoming data can streamline processes. Regular training sessions can help staff utilize these tools effectively, enhancing data-driven decision-making.

Legacy System Integration

To maximize value, IoT solutions for enterprises must integrate smoothly with numerous existing IT systems like ERP, CRM, e-commerce platforms, and data warehouses. This necessitates overcoming technical incompatibilities between old and new technologies and revising workflows to capitalize on real-time data. IoT should enhance other systems, not create data silos. Integration is an architectural challenge.

Adopting integration platforms as a service (iPaaS) can offer a flexible and scalable solution to connect disparate systems, allowing businesses to leverage IoT data across existing digital infrastructure.

[Also Read: Cloud ERP Integration: Costs, Types, Benefits]

IT/OT Alignment

In manufacturing and industrial settings, IoT requires information technology and operational technology teams to collaborate on a unified infrastructure for both digital and physical systems.

This may necessitate organizational changes to break down historical silos between the two groups. It also needs leadership commitment to onboard OT personnel on new technologies.

Interoperability Issues

The diversity of proprietary IoT hardware, network protocols, and software often lacks interoperability and universal standards. This makes integrating various IoT components complex, costly, and time-consuming. Perpetual retrofitting is required as vendors update products. Emerging IoT standards will ease, but not eliminate, this issue.

Collaborating with dedicated IoT software development organizations can help shape universal standards, making it easier to connect different technologies and reduce future technical issues.

Proof of RoI

Quantifying the return on investment and separating hype from reality remains difficult for some business leaders unfamiliar with IoT’s true potential and pitfalls. Careful project scoping, piloting, and tying use cases to measurable KPIs is essential to demonstrate concrete ROI before larger deployment. Progress may require educating leadership.

Security Risks

Increased connectivity and vast sensor networks expand the attack surface for hackers. Firms must secure IoT ecosystems, including device endpoints, data transmission, cloud platforms, and data use. IoT security requires multifaceted cyber strategies combining encryption, access controls, data masking, microsegmentation, and expert monitoring to safeguard systems and data.

Investing in specialized IoT security solutions and conducting regular security training for staff can help mitigate risks, ensuring the integrity of IoT devices and data.

Lack of Internal Expertise

As an emerging technology, there is a shortage of workers skilled in IoT hardware, connectivity, data science, analytics, application development, and cybersecurity. Building expertise across these domains either requires extensive training or hiring scarce talent. Many organizations will choose to partner with specialized IoT vendors.

Immature Technology

While rapidly maturing, IoT for enterprise tech still has gaps in standards, security, bandwidth, analytics, and other areas that create challenges in scaling. Edge computing architectures are evolving to address latency and bandwidth constraints. As platforms mature, capabilities will improve.

Cultural Resistance

Adjusting policies, procedures, workflows, and corporate culture to take advantage of real-time IoT data represents a major change. A lack of buy-in at all levels and ineffective change management can lead organizations to underutilize or resist IoT capabilities.

Implementing a comprehensive change management strategy that includes clear communication, training, and involvement from all levels of the organization can overcome resistance.

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Steps for Enterprise IoT Application Development

Developing an effective IoT solution development for enterprises requires focusing simultaneously on technology implementation and aligning IoT with broader strategic business goals. Follow these recommended steps for enterprise IoT solutions development.

A Step-by-Step Process to Develop an Enterprise IoT App

App Conceptualization

Begin the enterprise IoT application development process by understanding the business objectives, potential IoT use cases, and the impact on existing processes and systems. This phase involves strategic planning and conceptualizing the solution to align with business goals.

Requirements Analysis

Conduct a thorough feasibility study to evaluate technical and economic aspects. Gather requirements from all stakeholders to ensure the solution meets business needs, user expectations, and technical constraints.

IoT Platform Selection

Choose an IoT platform that best fits the project’s requirements. Considerations include compatibility with existing infrastructure, scalability, security features, and support for analytics.

UI/UX Design

Design the IoT system architecture, including device selection, data flow diagrams, and the integration architecture with existing enterprise systems. This phase requires careful planning to ensure scalability, security, and efficient data management.

Prototyping and Validation

Develop a prototype to validate the concept with stakeholders. This stage helps in identifying potential issues early and refining the user experience.

Development

Begin the development phase, focusing on building the IoT application, integrating it with selected devices, and ensuring seamless communication between the IoT platform and enterprise systems. Agile practices can be beneficial here for iterative development and testing.

Testing and Quality Assurance

Conduct comprehensive testing, including unit testing, integration testing, system testing, and security testing, to ensure the application meets all requirements and is free of vulnerabilities.

Deployment and Launch

Deploy the application in a controlled environment to monitor its performance and fix any issues before a full-scale rollout. Plan the deployment carefully to minimize disruption to existing operations.

Training and Support

Provide training to end-users and IT staff to ensure they are equipped to use and maintain the new system. Establish support processes to address any issues post-deployment.

Continuous Maintenance and Optimization

After deployment, continuously monitor the system to optimize performance, address any emerging issues, and update the system as needed based on user feedback and technological advancements.

Understanding Enterprise IoT Software Development Cost

The cost of building and deploying IoT for enterprise solutions varies substantially depending on the scale, complexity, number of use cases, endpoint volume, and required capabilities. While the exact cost can vary significantly based on the specific requirements and scale of the project, industry estimates suggest that the typical cost range for developing an enterprise IoT software solution falls between $35,000 to $150,000 for small to medium-sized deployments and $200,000 to $350,000 or more for large-scale, complex implementations.

Let’s look at some of the key factors that influence overall IoT software development costs in detail below.

Factors Affecting the Cost to Develop an Enterprise IoT Software

Scope of Use Cases

The more expansive the project scope across business units and objectives, the greater the costs. A single-site manufacturing efficiency initiative entails lower costs than a global logistics tracking rollout impacting supply chain, field operations, and customer experience. Prioritizing use cases delivers the best ROI.

Number of Endpoint Sensors

Adding more IoT sensors and endpoints monitoring equipment, facilities or products proportionally increases hardware, connectivity, and data management expenses. Complexity also rises with more data signals to process and analyze. A focused approach is best for initial projects.

Edge vs. Cloud Data Processing

Sending all sensor data to the cloud for processing requires high bandwidth and latency considerations. Edge computing architectures that filter and analyze data locally can lower data transmission costs but add to hardware needs. The right hybrid model balances both.

Legacy Systems Integration

Connecting siloed data systems like ERP and CRM to IoT platforms to contextualize IoT data adds to the overall IoT for enterprise integration costs. The more legacy systems involved, the more complex and expensive this becomes. Starting with greenfield implementations is easier.

Custom Software Development

IoT solutions for enterprises require customized dashboards, analytics, automation, and control software. More complex business logic, algorithms, and functionality lead to an overall increase in the enterprise IoT software development costs.

IoT Platform Setup

Major cloud providers offer IoT platforms-as-a-service with different pricing models based on endpoints, data processing, and features. Open-source software offers more customization but demands technical skills for implementation and management.

Data Storage Needs

The rate of data aggregation from devices and sensors determines cloud storage needs. High-frequency temperature readings from thousands of sensors require more storage and expense than occasional equipment telemetry. Compression and selective data transfer optimize storage.

Security Requirements

Encrypting data, access controls, and hardened devices add overhead but are essential for IoT security. Rigorous penetration testing and audits add labor costs but reduce risk. Updates and monitoring for threats are also ongoing costs.

Geographic Distribution

Connectivity costs are higher for global deployments, and distributed infrastructure is required for LAN and WAN networks. Multi-region rollouts multiply labor, security, maintenance, and platform licensing expenses.

How Can Appinventiv Help You leverage Enterprise IoT for Your Business Growth

We hope our blog has provided you with a comprehensive understanding of Enterprise IoT and its transformative potential for businesses seeking operational excellence, informed decision-making, and sustained growth. Investing in IoT for your enterprise opens the door to a future of innovation and competitive advantage.

At Appinventiv, we leverage our extensive expertise in enterprise IoT services to elevate your business operations, ensuring they’re not only more efficient and productive but also sustainable.

Our team ensures seamless integration with an array of cloud platforms including AWS, Microsoft Azure, Google Cloud, and custom solutions tailored to your needs. With a focus on secure and efficient IoT communication protocols, we establish secure connections for devices, enabling robust data collection, storage, analysis, and management capabilities.

As a dedicated IoT app development company, we are dedicated to optimizing the functionality of your IoT devices through the integration of AI technology, which facilitates efficient edge processing capabilities.

Being a renowned enterprise software development company, our team of experienced data science professionals specializes in creating and implementing machine learning models directly onto devices, resulting in instantaneous data processing and valuable insights.

Get in touch with our experienced enterprise IoT software developers to craft a tailored IoT solution that drives innovation and growth for your enterprise.

FAQs

Q. How can businesses leverage Enterprise IoT for sustained growth?

A. IoT solutions enable enterprises to collect and analyze data from various sources in real-time, providing valuable insights into operations, customer behavior, and market trends. This data-driven approach empowers organizations to make informed decisions, optimize processes, and respond quickly to changing conditions.

Q. What factors impact the price of implementing IoT in enterprises?

A. The primary factors influencing the cost of IoT for enterprise implementation include the project scope and complexity, hardware requirements (devices, sensors, gateways), software and platform licensing fees, integration with existing systems, customization needs, and ongoing support and maintenance costs.

Q. What are the latest Enterprise IoT trends?

A. Major enterprise IoT trends involve adopting 5G connectivity, e­dge computing structures, utilizing AI for improved analytics, inte­grating blockchain for cybersecurity, automating tasks with robotics and wearable­s, and harmonizing IoT data with sustainability objectives. These­ trends aim to boost bandwidth, cut costs, apply sophisticated analytics, and connect IoT to digital transformation.

Q. How does Enterprise IoT improve decision-making processes within organizations?

A. IoT device­s and sensors give businesse­s real-time insights into operations through data colle­ction and analysis. Organizations can use enterprise IoT solutions to improve production processes and supply chain management, optimize resources, and respond rapidly to changing conditions.

THE AUTHOR
Sudeep Srivastava
Co-Founder and Director
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