We’re proud to announce that Perficient has been named a 2025 CRN IoT Innovator, a prestigious recognition that celebrates solution providers leading the way in delivering impactful Internet of Things (IoT) solutions in the enterprise market across industries. This honor underscores our commitment to helping clients bridge the gap between the physical and digital worlds through cutting-edge IoT strategies and technologies.

CRN’s annual IoT Innovators list highlights companies that are shaping the future of enterprise IoT, with solutions spanning connected field operations, AI-powered analytics, digital twins, and edge computing. In the article, the senior editor Dylan Martin remarked:

”Perficient is delivering transformative business outcomes for customers with its end-to-end IoT solutions. In the automotive industry, the St. Louis-based solution provider offers consulting services for the design and integration of advanced driver assist, autonomous, multi-cloud and software-defined vehicle capabilities.”

Perficient’s inclusion reflects our leadership in deploying transformative IoT solutions that drive measurable outcomes, especially in the automotive and manufacturing sectors where data and AI innovation is not just a goal, but a necessity.

Why Perficient Stands Out

In our recent study of nearly 700 consumers in the U.S., 61% of participants in the 29 – 44 year old age bracket responded that they’d want their vehicles to communicate and interact with their in-home devices. This overwhelmingly positive response to connected capabilities across the automotive and manufacturing market reveals a massive opportunity for enterprises to tap into new revenue streams and improved customer experiences.

Perficient is poised to support these enterprises as they continue to innovate in the IoT space. Our approach combines deep industry expertise, AI-first strategies, and robust engineering capabilities to help clients unlock new efficiencies, improve product quality, and deliver exceptional customer experiences.

Recently, Perficient launched:

• Proprietary research on the connected products market meant to inform strategy for organizations across industries delving into and innovating in the IoT space
• Several Strategic Positions on the latest industry innovations around connected products and vehicles, electrification, EV charging, and autonomous driving
• Solutions that utilize connected capabilities and telemetry data to improve customer experience and drive new revenue streams like Battery Passports

Further, Perficient was named a Major Player in the IDC MarketScape: Worldwide IT and Engineering Services for Software-Defined Vehicles 2025 Vendor Assessment (doc # US51813124, September 2025).

In automotive, we partner with 7 of the top 10 OEMs to modernize operations and accelerate innovation. Our IoT solutions support everything from connected vehicle platforms and advanced driver assistance systems (ADAS) to dealer service integration and mobility-as-a-service models. We help OEMs, suppliers, and dealers create seamless, personalized experiences for vehicle owners and passengers, while optimizing design, manufacturing, and service operations.

In the broader manufacturing market, our IoT offerings empower clients to build smart factories and resilient supply chains. From digital twins and collaborative robotics to predictive maintenance and connected shop floor monitoring, we enable manufacturers to gain real-time visibility into assets, reduce downtime, and improve quality assurance. Our solutions are designed to meet the demands of a rapidly evolving landscape shaped by 5G, sustainability goals, and workforce transformation.

An AI-First Future-Ready Partner

We’re a global, AI-first, digital consultancy with thousands of skilled strategists and technologists in the U.S., Latin America, India, Europe, and around the world. We’re transforming how the world’s most admired brands connect with customers and grow their business. As an AWS Advanced Service Partner, member of Microsoft’s 2025-2026 AI Inner Circle, and collaborative partner to AI innovators from Writer and Databricks to Salesforce, Perficient is uniquely positioned to deliver scalable, secure, and intelligent IoT solutions. Our strategic partnerships and technical depth allow us to stay ahead of emerging trends and deliver value that lasts.

Whether you’re an automotive OEM looking to redefine mobility or a manufacturer seeking to build smarter machines, Perficient is your trusted partner for IoT transformation.

Learn more about our industry recognitions and explore our AI in automotive or manufacturing expertise.

In today’s world, the Internet of Things (IoT) is revolutionizing industries across the globe by connecting devices, systems, and people in ways that were once unimaginable. From smart homes to advanced manufacturing, IoT is creating new opportunities for innovation, efficiency, and data-driven decision-making. At the forefront of this transformation is Microsoft Azure, a cloud computing platform that has become a powerhouse for IoT operations.

In this blog, we’ll dive into the essentials of Azure IoT operations, how it simplifies and optimizes IoT workflows, and the key features that make it the go-to solution for businesses looking to scale their IoT systems.

What is Azure IoT?

Azure IoT is a set of services, solutions, and tools from Microsoft that allow businesses to securely connect, monitor, and control IoT devices across various environments. Azure IoT offers comprehensive capabilities for deploying IoT solutions, managing the entire device lifecycle, and providing data-driven insights that enhance decision-making processes.

At the core of Azure IoT is the ability to integrate IoT devices with cloud-based analytics, machine learning, and data processing tools, enabling businesses to leverage real-time data for more informed decisions.

Why Azure for IoT Operations?

Microsoft Azure is one of the leading cloud platforms that offer robust, scalable, and secure solutions for managing IoT operations. It is built on a foundation of powerful infrastructure that allows organizations to quickly deploy IoT systems and scale them based on evolving business needs. Here’s why businesses choose Azure for their IoT operations:

Scalability

Azure IoT can support millions of devices, allowing businesses to scale their IoT systems from a handful of devices to a vast ecosystem of connected devices across different locations. This scalability ensures that companies can grow their IoT initiatives without being limited by infrastructure constraints.

Security

Security is a major concern when managing IoT devices, as these devices are often vulnerable to cyberattacks. Azure IoT integrates comprehensive security measures, including device identity management, encryption, secure data transmission, and compliance with industry standards. This ensures that IoT operations are protected from potential threats.

Data Analytics and Insights

Azure provides a suite of analytics tools, including Azure Machine Learning, Power BI, and Azure Stream Analytics, that enable businesses to analyze data generated by their IoT devices in real-time. This enables predictive maintenance, real-time monitoring, and data-driven decision-making, ultimately improving operational efficiency.

Integration with Other Microsoft Services

Azure IoT seamlessly integrates with other Microsoft tools and services, such as Office 365, Microsoft Teams, and Azure Active Directory. This enables businesses to seamlessly integrate IoT data into their existing workflows and processes, fostering collaboration and facilitating more informed business operations.

Cross-Platform Compatibility

Azure IoT supports a wide variety of devices, operating systems, and protocols, making it a versatile solution that can integrate with existing IoT deployments, regardless of the technology stack. This interoperability allows businesses to get the most out of their IoT investments.

Key Components of Azure IoT Operations

Azure IoT comprises various tools and services that address different aspects of IoT operations, ranging from device connectivity to data processing and analytics. Let’s explore some of the key components:

Azure IoT Hub

At the heart of Azure IoT operations is Azure IoT Hub, a fully managed service that enables secure and reliable communication between IoT devices and the cloud. It allows businesses to connect, monitor, and control millions of IoT devices from a single platform.

The IoT Hub provides two-way communication, allowing devices to send data to the cloud while also receiving commands. This bi-directional communication is crucial for remote monitoring, updating device configurations, and managing device health in real-time.

Azure Digital Twins

Azure Digital Twins is an advanced service that enables businesses to create digital models of physical environments. These models are used to visualize and analyze IoT data, providing a more comprehensive understanding of how devices and systems interact in the real world.

By utilizing Azure Digital Twins, organizations can optimize their operations, enhance asset management, and simulate scenarios for predictive maintenance and improved energy efficiency.

Azure IoT Edge

Azure IoT Edge enables businesses to run Azure services, including machine learning, analytics, and AI, directly on IoT devices at the edge of the network. This reduces latency and enables faster decision-making by processing data locally, rather than relying solely on cloud-based processing.

IoT Edge is ideal for scenarios where real-time data processing is critical, such as autonomous vehicles, industrial automation, or remote monitoring of remote assets.

Azure IoT Central

Azure IoT Central is a fully managed IoT SaaS (Software as a Service) solution that simplifies the deployment, management, and monitoring of IoT applications. With IoT Central, businesses can quickly deploy IoT solutions without requiring deep technical expertise in cloud infrastructure.

It offers an intuitive interface for managing devices, setting up dashboards, and creating alerts. IoT Central significantly reduces the complexity and time required to deploy IoT systems.

Azure Time Series Insights

Azure Time Series Insights is a fully managed analytics and storage service for time-series data. It is specifically designed for handling large volumes of data generated by IoT devices, such as sensor data, telemetry data, and event logs.

Time Series Insights offers powerful visualization and querying capabilities, enabling businesses to uncover trends and patterns in their IoT data. This is especially useful for monitoring long-term performance, detecting anomalies, and optimizing processes.

Optimizing IoT Operations with Azure

Azure IoT operations can be further optimized by integrating advanced technologies such as Artificial Intelligence (AI) and Machine Learning (ML). These technologies enable businesses to collect and store IoT data, as well as derive actionable insights from it.

Predictive Maintenance

By analyzing IoT data, Azure IoT can predict equipment failures before they occur. Using machine learning algorithms, businesses can identify patterns that indicate potential breakdowns and perform maintenance only when necessary, reducing downtime and maintenance costs.

Smart Automation

Azure IoT enables businesses to automate processes based on real-time data. For example, in smart factories, devices can automatically adjust production lines based on environmental conditions, inventory levels, or supply chain disruptions, increasing efficiency and reducing human error.

Energy Management

Azure IoT can help businesses optimize energy usage by continuously monitoring energy consumption and adjusting operations accordingly. Smart building solutions, for example, can automatically control lighting, heating, and cooling systems to reduce energy waste and lower costs.

Use Case

Azure IoT Operations Configuration Example: A Step-by-Step Guide

When configuring Azure IoT operations, you’re setting up a system where devices can securely connect to the cloud, send telemetry data, and receive commands for actions. Let’s walk through a practical configuration example using Azure IoT Hub, a key service in Azure IoT operations by following below link.

Tutorial: Send telemetry from an IoT Plug and Play device to Azure IoT Hub

Conclusion

Azure IoT operations are transforming how businesses leverage the Internet of Things to improve efficiency, enhance customer experiences, and unlock new revenue streams. With its powerful cloud infrastructure, end-to-end solutions, and integration with Microsoft’s suite of tools, Azure is a leading choice for businesses looking to capitalize on the potential of IoT.

By deploying Azure IoT, companies can connect their devices, analyze real-time data, optimize operations, and make data-driven decisions that enhance their bottom line. Whether you’re starting small with a few connected devices or deploying large-scale, enterprise-wide IoT solutions, Azure provides the tools, security, and scalability needed to succeed in the world of connected technology.

As IoT continues to evolve, Azure will undoubtedly remain at the forefront of this exciting and transformative field, helping businesses drive innovation and stay competitive in an increasingly connected world.

In today’s hyper-connected world, the Internet of Things (IoT) is transforming industries, from smart manufacturing to intelligent healthcare. However, the real potential of IoT is to connect continuously with enterprise systems, providing real-time insights and automating. This is where MuleSoft’s Anypoint Platform comes in, a disturbance in integrating IoT units and API to create an ecosystem. This blog explains how MuleSoft sets the platform for connection and introduces a strong basis for IoT and API integration that goes beyond the specific dashboard to offer scalability, safety, and efficiency.

Objective

In this blog, I will show MuleSoft’s ability to integrate IoT devices with enterprise systems through API connectivity, focusing on real-time data processing. I will provide an example of how MuleSoft’s Anypoint Platform connects to an MQTT broker and processes IoT device sensor data. The example highlights MuleSoft’s ability to handle IoT protocols like MQTT and transform data for insights.

How Does MuleSoft Facilitate IoT Integration?

The MuleSoft’s Anypoint Platform is specific to the API connection, native protocol support, and a comprehensive integration structure to handle the complications of IoT integration. This is how MuleSoft IOT does the integration comfortably:

1. API Connectivity for Scalable Ecosystems

MuleSoft’s API strategy categorizes integrations into System, Process, and Experience APIs, allowing modular connections between IoT devices and enterprise systems. For example, in a smart city, System APIs gather data from traffic sensors and insights into a dashboard. This scalability avoids the chaos of point-to-point integrations, a fault in most visualization-focused tools.

2. Native IoT Protocol Support

IoT devices are based on protocols such as MQTT, AMQP, and CoAP, which MuleSoft supports. Without middleware, this enables direct communication between sensors and gateways. In a scenario, MuleSoft is better able to connect MQTT data from temperature sensors to a cloud platform such as Azure IoT Hub than other tools that require custom plugins.

3. Real-Time Processing and Automation

IoT requires real-time data processing, and MuleSoft’s runtime engine processes data streams in real time while supporting automation. For example, if a factory sensor picks up a fault, MuleSoft can invoke an API to notify maintenance teams and update systems. MuleSoft integrates visualization with actionable workflows.

4. Pre-Built Connectors for Setup

MuleSoft’s Anypoint Exchange provides connectors for IoT platforms (e.g., AWS IoT) and enterprise systems (e.g., Salesforce). In healthcare, connectors link patient wearables to EHRs, reducing development time. This plug-and-play approach beats custom integrations commonly required by other tools.

5. Centralized Management and Security

IoT devices manage sensitive information, and MuleSoft maintains security through API encryption and OAuth. Its Management Center provides a dashboard to track device health and data flows, offering centralized control that standalone dashboard applications cannot provide without additional infrastructure.

6. Hybrid and Scalable Deployments

MuleSoft’s hybrid model supports both on-premises and cloud environments, providing flexibility for IoT deployments. Its scalability handles growing networks, such as fleets of connected vehicles, making it a future-proof solution.

Building a Simple IoT Integration with MuleSoft

To demonstrate MuleSoft’s IoT integration, below I have created a simple flow in Anypoint Studio that connects to an MQTT Explorer, processes sensor data, and logs it to the dashboard integration. This flow uses a public MQTT Explorer to simulate IoT sensor data. The following are the steps for the Mule API flow:

Step 1: Setting Up the Mule Flow

In Anypoint Studio, create a new Mule project (e.g., ‘IoT-MQTT-Demo’). Design a flow with an MQTT Connector to connect to an explorer, a Transform Message component to process data, and a Logger to output results.

Step 2: Configuring the MQTT Connector

Configure the MQTT Connector properties. In General Settings, configure on a public broker (“tcp://test.mosquitto.org:1883”). Add the topic filter “iot/sensor/data” and select QoS “AT_MOST_ONCE”.

Step 3: Transforming the Data

Use DataWeave to parse the incoming JSON payload (e.g., ‘{“temperature”: 25.5 }’) and add a timestamp. The DataWeave code is:

“`

%dw 2.0

output application/json

{

sensor: “Temperature”,

value: read(payload, “application/json“).temperature default “”,

timestamp: now()

}

“`

Step 4: Connect to MQTT

                Click on the Connections and use the credentials as shown below to connect to the MQTT explorer:

 Step 5: Simulating IoT Data

Once the MQTT connects using an MQTT Explorer, publish a sample message ‘{“temperature”: 28 }’ to the topic ‘iot/sensor/data’, sending to the Mule flow as shown below.

Step 6: Logging the Output

Run the API and publish the message from the MQTT explorer, and the processed data will be logged into the console. Below shows an example log:

The above example highlights MuleSoft’s process for connecting IoT devices, processing data, and preparing it for visualization or automation.

Challenges in IoT Integration and MuleSoft’s Solutions

IoT integration faces challenges:

• Device and Protocol Diversity: IoT ecosystems involve different devices, such as sensors or gateways, using protocols like MQTT or HTTP with different data formats, such as JSON, XML, or binary.
• Data Volume and Velocity: IoT devices generate high volumes of real-time data, which requires efficient processing to avoid restrictions.
• Security and Authentication: IoT devices are unsafe and require secure communications like TLS or OAuth for device authentication.
• Data Transformation and Processing: IoT data sends binary data, which requires transformation from Binary to JSON and needs improvement before use.

The Future of IoT with MuleSoft

The future of IoT with MuleSoft is promising. MuleSoft uses the Anypoint Platform to solve critical integration issues. It integrates different IoT devices and protocols, such as MQTT, to provide data flow between ecosystems. It provides real-time data processing and analytics integration. Security is added with TLS and OAuth.

Conclusion

MuleSoft’s Anypoint Platform reviews IoT and API integration by providing a scalable, secure, real-time solution for connecting devices to enterprise systems. As I showed in the example, MuleSoft processes MQTT-based IoT data and transforms it for useful insights without external scripts or sensors. By addressing challenges like data volume and security, MuleSoft provides a platform to build IoT ecosystems that provide automation and insights. As IoT keeps growing, MuleSoft’s API connectivity and native protocol support establish it as an innovation, with new smart city, healthcare, and more connectivity. Discover MuleSoft’s Anypoint Platform to unlock the full potential of your IoT projects and set the stage for a connected future.

Read our connected products research.

Consumer and commercial demand for connected products has risen steadily by 15% since 2000 and is projected to grow another 14% by 2027 according to projections by IoT Analytics Gmbh. Features that were once considered nice to have or premium functionality are now table stakes. This trend indicates a time sensitive opportunity for manufacturers to forge new avenues of revenue generation. It is therefore crucial for manufacturers to continue pushing the envelope of capabilities the market has come to expect, depend on, and demand more of in the future.   

Perficient recognizes the value of thought leadership when competing for market share in a growing market.  To provide key insights that would inform connected product manufacturers’ strategies going forward, we surveyed end users and manufacturers of connected products to discover the factors impacting their sales, user behavior, and future trajectory. Over 1,300 responses across industries, departments, and seniority levels reveal intriguing commonalities and discrepancies.  We share in this piece some of the insight we gained from researching our survey returns.      

Explore our manufacturing industry expertise.

AI & ML is Where Manufacturer, Consumer, and Commercial User Interests Converge

Currently, emerging innovations enable completely new ways of leveraging connected products. Analysis of our results across manufacturers, commercial users, and consumers revealed that AI & ML are recognized by all groups as important, particularly with a market agreement on healthcare, home, and automotive automation and monitoring.     

AI, ML, and 5G technology enable the next era of capability extending well beyond connected thermostats and remote start automobiles many of us have adopted already.  Imagine an AI chatbot on your screen that can answer questions about how much gas money you should budget for your next road trip based on your route and vehicle mileage, fuel efficiency, and localized fuel costs by your designated octane rating.   

Differing Perspectives on Interoperability 

Our research uncovered a surprising gap between manufacturers and end-users in the perception of product interoperability within connected ecosystems. There was a strong proportional alignment among all manufacturer respondents on their products connecting “very well” or “well,” while a disproportionate number of responses from the market indicate a potential disconnect when it comes to products that connect “somewhat well.” 

Knowledge is power.  One of our hypotheses posits that the disconnect between manufacturers and their end users is lack of awareness of the connected features already enabled in their current devices.  This not only impedes demand-side innovation but also inhibits adoption of new technologies because upgrade costs may be perceived as “not worth it.”  This stimulated our curiosity to investigate the considerations our survey results indicate impact adoption.     

Explore our Connected Product Strategic Position.

How Does This Affect Connected Product Strategy? 

The above insights only cover a few of the many key takeaways that our team was able to derive from the research, but even diving into these alone will help uncover a wealth of opportunity. The results from our research highlight the clear need to take a step back and assess more deeply which areas of connected product innovation require more investment, such as rethinking data collection and utilization, product experience, and unlocking new business models. 

Opportunity for Improved Product Experience, Data Strategy, and Revenue Streams

There are many opportunities to improve connected product functionality, usability, and transparency. For example, a companion app can make it easier to change settings and improve personalization from the app instead of directly interfacing the product. The app would also enable remote monitoring, which can enhance safety and convenience for consumers who want to check in on their property or devices while away or get alerts for hazards like fire, carbon monoxide, open doors and windows, or air quality-related issues. ​ 

Not only should manufacturers consider how connected capabilities and opportunities can improve the user experience but also look internally about how they’re organizing and utilizing incoming data from those products. For example, automotive OEMs can create automated, cloud-agnostic data processing platforms that support that help improve the process of making cars by studying telemetry data driver behavior and machinery functionality insights.  In collecting and analyzing this data, manufacturers can then use it to inform new product features or improvements to issues like design flaws or poor user experience.  

Ultimately, manufacturers should look closely at exploring new revenue streams using their improved data strategy and interfaces to increase profitability and enhance customer loyalty. Making some features freely available and upgrades available through subscriptions, for example, is an opportunity to improve user experience and customer retention while bringing in recurring revenue. 

Do these insights resonate with you or ignite curiosity?  Download our guide outlining the research and   reach out to us  today to schedule a workshop or briefing to collaborate on how all of our insights and more can inform your connected products strategy.   

In the latest episode of our podcast, we dive into the world of communications, media, and technology (CMT). Our guest, Kevin Colletti, director of digital strategy and consulting at Perficient, sheds light on how these once-distinct industries are rapidly converging in the digital age.

The lines between telecom providers, media companies, and tech giants are blurring. For example, when you sign up for a phone plan, you might also get cloud storage and a streaming service bundle. This convergence isn’t just changing how we consume content and services; it’s reshaping entire business models.

But it’s not all smooth sailing. CMT companies face unique challenges, from meeting sky-high customer expectations for connectivity and security to keeping pace with disruptive technologies. The pressure to innovate while maintaining core services is intense.

In the B2B world, we’re seeing exciting developments like 5G-enabled smart farming and fixed wireless access for small businesses. The Internet of Things (IoT) is connecting everything from smartphones to industrial machinery, opening up vast new possibilities.

Key takeaways for businesses? As Kevin aptly puts it, “Don’t follow the shiny object. Understand the shiny object, how it applies to you and how you could leverage it or leapfrog it.”

Listen now on your favorite podcast platform or visit our website.

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Meet our Guest

Kevin Colletti, Kevin Colletti, Director of Strategy and Consulting for Perficient

Kevin Colletti is the director of digital strategy and consulting at Perficient. He has extensive experience working with client senior management teams to develop innovative digital strategies that deliver measurable results. He thrives on creating simplified solutions to complex business problems. Prior to joining Perficient, Kevin held roles including CEO at both a digital agency and a software company as well as head of eBusiness strategy for a Fortune Global 500 company. operations.

Connect with Kevin

Meet the Host

Jim Hertzfeld is Area Vice President, Strategy for Perficient.

For over two decades, he has worked with clients to convert market insights into real-world digital products and customer experiences that actually grow their business. More than just a strategist, Jim is a pragmatic rebel known for challenging the conventional and turning grand visions into actionable steps. His candid demeanor, sprinkled with a dose of cynical optimism, shapes a narrative that challenges and inspires listeners.

Connect with Jim:

LinkedIn | Perficient

In this episode of “What If? So What?” Jim talks with Neelima Sharma, SVP of ecommerce, digital, and technology at Lowe’s about the challenges and successes of transforming the retail industry through digital innovation. Neelima highlights the importance of teamwork, trust, and a customer-centric approach in driving the company’s growth and also emphasizes the significance of personalization and building long-term relationships with customers. The conversation touches on topics such as the impact of COVID-19 on retail, the role of AI and human intuition in decision making, and the importance of accurate inventory management. The conversation provides valuable insights into the strategies and mindset required for successful digital transformation in the retail industry.

Listen now on your favorite podcast platform or visit our website.

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Meet our Guest

Neelima V. Sharma,  Senior Vice President, Digital Commerce and Technology

Neelima Sharma, SVP of digital commerce and technology at Lowe’s, oversees the company’s online business and customer- and vendor-facing technologies. She enhances omnichannel experiences, core merchandising, and competitive pricing strategies. With more than 25 years of experience, Neelima has driven significant tech advancements at Lowe’s, including migrating Lowes.com to Google Cloud, and previously led Staples’ $8 billion B2B ecommerce tech division. Her career also includes impactful roles at JP MorganChase and Deloitte.

Neelima holds a bachelor’s degree in computer science from the University of Delhi and a master’s from the University of Indore. Recognized as a leader in retail technology, she was named among the Top Women in Retail Tech by Retail Info Systems in 2023 and honored as a Top Woman in Hardware & Building Supply by HBS Dealer. Neelima is an adviser to tech startups, serves on the board of Charlotte Center City Partners, and co-chairs Lowe’s Asia Pacific business resource group.

Connect with Neelima

Meet the Host

Jim Hertzfeld is Area Vice President, Strategy for Perficient.

For over two decades, he has worked with clients to convert market insights into real-world digital products and customer experiences that actually grow their business. More than just a strategist, Jim is a pragmatic rebel known for challenging the conventional and turning grand visions into actionable steps. His candid demeanor, sprinkled with a dose of cynical optimism, shapes a narrative that challenges and inspires listeners.

Connect with Jim:

LinkedIn | Perficient

In the latest episode of “What If, So What?” we are joined by Claus Torp Jensen, a pioneer in the realm of digital transformation. Claus, who has extensive experience in roles including chief architect and chief digital officer at companies like IBM and CVS, shares invaluable insights into the evolving technologies of ambient computing and digital twins.

Ambient computing, as Claus describes, is about creating a seamless integration of technology into our daily lives. It’s not just about smart devices but about creating an environment where technology acts as a personal life assistant –silent yet proactive. Claus explains how this technology is not just futuristic but is already embedded in various industries, enhancing operational efficiency and personalizing user experiences.

Digital twins, on the other hand, offer a digital representation of physical systems, providing businesses with critical data to predict future scenarios and effectively plan for them. This technology, Claus says, can transform industries by offering a blueprint for decision-making and preemptive action.

Join us as Claus Torp Jensen explains these concepts using real-world examples and discusses the broader implications for industries and personal lifestyles alike. If you’re interested in how technology is subtly yet significantly transforming our world, this episode is a must-listen.

Listen now on your favorite podcast platform or visit our website.

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Meet our Guest

Claus Torp Jensen, Chief Storyteller and Digital Transformation Leader

Claus Torp Jensen is a technologist turned chief storyteller and digital transformation leader. As a proactive change agent, he has expanded his horizons by working across two countries and three diverse industries. Driven by a commitment to purpose and real-world impact, his non-linear career path is fueled by opportunities to enact positive changes —enhancing teams, processes, technology, and business operations.

A lifelong learner with a deep-seated passion for healthcare, research, and education, Claus actively contributes as a speaker, and mentor and has authored the books “Whole Person Care for Dummies” and “Digital Transformation for Dummies”. Outside of his professional pursuits, he cherishes traveling with his family, exploring new cultures, and gaining global perspectives.

Connect with Claus

Meet the Host

Jim Hertzfeld is Area Vice President, Strategy for Perficient.

For over two decades, he has worked with clients to convert market insights into real-world digital products and customer experiences that actually grow their business. More than just a strategist, Jim is a pragmatic rebel known for challenging the conventional and turning grand visions into actionable steps. His candid demeanor, sprinkled with a dose of cynical optimism, shapes a narrative that challenges and inspires listeners.

Connect with Jim:

LinkedIn | Perficient

In a world where technology evolves at lightning speed, staying ahead of the curve is not just important— it’s essential. In the latest episode of our “What If, So What?” podcast we dive deep into the tech trends reshaping industries in 2024. Join our host, Jim Hertzfeld, as he sits down with Mike Kosiek, a visionary technology product director from a Fortune 100 retailer, to explore the innovations that will define the next decade.

From Theory to Application

Mike brings a unique perspective to the table, blending deep industry knowledge with practical insights. The episode covers a range of transformative technologies, from the expanding capabilities of augmented reality to the revolutionary potential of blockchain across global supply chains.

Why Listen?

Whether you’re a tech enthusiast or a business leader, the conversation provides insights into how emerging technologies can drive significant growth and efficiency. Mike’s expertise in product incubation illuminates not just “the what” of these technologies but also ” the how” of integrating them into everyday business and our personal lives.

Whether you’re looking to enhance your personal knowledge or guide your organization through upcoming tech shifts, this episode is a must listen.

Listen now on your favorite podcast platform or visit our website.

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Meet our Guest

Mike Kosiek, Technology Product Director at a Fortune 100 Retailer

Mike Kosiek is a leader in digital product incubation and strategy based in greater Minneapolis-St. Paul, Minnesota. Known for his customer-centric approach to technology, Mike brings extensive retail experience to his role. He thrives on guiding his team as it transforms bold, innovative ideas into tangible outcomes. Creative and passionate about emerging technologies, he is dedicated to empowering his team to excel and is committed to enhancing his storytelling skills.

Outside of his professional life, Mike is a busy partner and father of three. He stays active, enjoys the outdoors, and co-hosts a golf and fantasy sports podcast titled “Reading the Green.”

Connect with Mike

Meet the Host

Jim Hertzfeld is Area Vice President, Strategy for Perficient. For over two decades, he has worked with clients to convert market insights into real-world digital products and customer experiences that actually grow their business.

More than just a strategist, Jim is a pragmatic rebel known for challenging the conventional and turning grand visions into actionable steps. His candid demeanor, sprinkled with a dose of cynical optimism, shapes a narrative that challenges and inspires listeners.

Connect with Jim:

LinkedIn | Perficient

Imagine a world where roads are safer than ever! This could be possible thanks to an AI Testing Strategy by Perficient, which stands out as a trendsetter in innovation, driving solutions that revolutionize traffic management and road safety enforcement. Do you dare to step into this journey towards a safer and more efficient future? 

Join us as we explore the power of artificial intelligence to transform our roads and save lives! 

In advancing technology for safer roads, this AI Testing Strategy highlights innovative solutions aimed at enhancing traffic management and safety enforcement. Central to this initiative, there are two systems, one that handles the intrusion of lane enforcement and one that detects vehicle movement when the school bus stop arm is deployed. While both operate on artificial intelligence (AI) principles, the Lane Enforcement system specifically employs custom computer vision models to achieve its objectives. 

Lane Enforcement System 

Picture this: bustling city streets with designated lanes for public bus services. Unfortunately, these lanes often fall victim to unauthorized vehicles, disrupting traffic flow and posing safety hazards. Enter the Lane Enforcement system, designed to identify and rectify such infringements in real time. This is accomplished through a meticulous analysis of each frame captured by live cameras. 

Challenges 

The implementation of the Lane Enforcement system is not without its challenges: 

• Nondeterministic Outputs: Variability in system outputs requires the establishment of thresholds for decision-making. 
• Data Collection: Accurate ground truth data is essential to minimize false positives, necessitating manual labeling. 
• System Integration: Coordinating the operation of multiple models within the broader system framework. 
• Testing and Evaluation: Rigorous testing procedures are essential to validate system performance and effectiveness. 

AI Testing Strategy 

By integrating AI into the Testing Strategy to address these challenges, we streamline testing processes, facilitate continuous integration, and improve test coverage, while maintaining high levels of quality and improving public safety: 

• MLOPS Integration: Leveraging Azure Machine Learning, a CI/CD pipeline facilitates continuous monitoring and evaluation of model performance metrics. 
• Comprehensive Dataset Definition: Real-world scenarios, including corner cases, are incorporated into the dataset to enhance testing coverage. 
• Integration Testing: Simulators are utilized to evaluate model inferences and their impact on system performance. 
• Automation of Metrics Gathering: Automated evaluation of system metrics ensures rapid feedback and detection of anomalies. 
• Test Coverage Enhancement: From unit tests to comprehensive component and end-to-end tests, the testing coverage is substantially increased. 

Conclusion 

This AI Testing Strategy by Perficient stands as a leading light of innovation in road safety enforcement, harnessing the power of AI-based solutions to mitigate traffic violations and improve public safety. Through a strong QA strategy testing and continuous refinement, this initiative exemplifies the fusion of technology and innovation for a safer and more efficient urban environment. 

In collaboration with Perficient, a leading digital consultancy recognized for its expertise in AI and data-driven solutions, this strategy has been able to push the boundaries of what is possible in traffic management and safety enforcement. Perficient’s dedication to excellence and cutting-edge technology has played a key role in this project’s success. 

As we continue to embrace advances in AI and machine learning, strategies like this, supported by industry leaders like Perficient, pave the way for a brighter and safer future on our roads. Together, we are shaping a world where technology not only improves efficiency but also saves lives. 

At the center of digital transformation, we face the exciting challenge of creating an ecosystem driven by high-performance, interconnected microservices developed in diverse languages such as Java, C#, JavaScript, and Python. At Perficient we extract the best of each language to shape an agile and efficient ecosystem. 

Capturing data in real time: IoT and Priority Security   

This dynamic environment is powered by microservices that capture data by integrating with devices through IoT (Internet of Things). The essence of our mission lies in building innovative products aimed to identify external threats, prioritizing the safety of vehicles, passengers, drivers, and pedestrians. Our cutting-edge tools, such as cameras and sensors, offer real-time tracking, supported by AI (artificial intelligence) image recognition.  

Hexagonal Architecture and DevSecOps: Fundamentals of our operation  

The state-of-the-art of our ecosystem is defined by a hexagonal architecture, domain-driven design, and event-driven architecture. This approach ensures that software is built with a ubiquitous language, simplifying functions so any team member can understand them. This results in scalable and flexible software, able to adapt to changing demands and decoupled to offer flexibility in services as the challenge arises. 

The scalability of our system extends to the cloud, working with providers such as Amazon AWS and Microsoft Azure in their commercial and government versions. This facilitates integration with various cloud services, from file storage to serverless services, databases and more, ensuring efficient and effective operation. 

Adopting the DevSecOps culture, we have implemented continuous integration and deployment practices, infrastructure as code and test automation. This combination of practices allows us to consistently add value with a predictable cadence, leading the delivery of advanced technological solutions. 

One of the critical areas of our work focuses on court cases, where we manage the capture, management, and disposition of evidence. This security challenge has led us to comply with rigorous standards such as SOC2, CJIS (criminal justice information) and OWASP-TOP10. 

In the vehicular domain, our systems, connected to the Azure cloud via IoT, search for incident-related license plates in real time. This capability allows immediate action to be taken, contributing to overall safety on the roads.  

Real-time visualization: Complete experience  

Real-time visualization via WebSockets offers a complete experience, displaying travel, vehicle information and all telemetry data. In the case of school buses, this technology ensures children’s safety by stopping and extending the “STOP” paddle, with IoT-connected cameras applying artificial intelligence to detect violations.  

In short, our safety ecosystem represents the convergence of innovation and advanced technology. At Perficient, we move forward into the future with the conviction that technology can transform security and efficiency in our daily lives. We build not just a technology ecosystem, but a safer, more secure and connected future for all. 

Vehicles today remind me of smartphones on wheels. When you get down to it, they are computers capable of software upgrades, navigation, sensing, and even entertainment through subscriptions or mobile apps. Automotive manufacturers are realizing that many young consumers are preferring frictionless and fully digital customer journeys as opposed to multiple lengthy in-person visits to the dealership. Of course, this does not mean that everyone wants to purchase vehicles online with 10 clicks, but it does mean that we must create experiences that modern consumers have come to expect.

Rapidly changing consumer preferences beg the question: how can OEMs and dealers stay relevant and continue providing top-notch customer experience? We’ve already been seeing innovations like virtual test drives, where a consumer can get a good feeling of what it is like to drive a particular vehicle online before visiting in person. This digital offering proves that many OEMs today understand they must give consumers choices and be able to satisfy their preferences.

Extending Digital-First to Vehicles

Beyond digital offerings from the dealership, the vehicles themselves must become digital-first. We all remember when new vehicles had internet installed, setting the foundation for many capabilities to come. Not only can drivers now use GPS navigation, but also connect their vehicles to their phones, access entertainment, and work on the go. Many drivers now take voice calls and texting through their vehicles while driving for granted. Yet, this is still just the beginning and there will be a lot more change to come.

Adding Vehicles to IoT

Naturally, what’s next is having your vehicle be connected to a comprehensive Internet of Things (IoT), communicating with other vehicles, buildings, infrastructure, and more. Connected vehicles will dramatically change the experience of driving, impacting the way we think about traffic, accidents, and commuting, and in some ways changing major aspects of our lives. From fleet management to school buses, IoT will touch everything transportation related. It will even improve the maintenance and management of fleets and commercial vehicles.

At the same time, these smart vehicles can communicate with other connected vehicles (V2V) over the public/federally owned dedicated short-range communication spectrum (DSRC), through cellular-based communications technology (C-V2X), and with smart city infrastructure (V2I) through machine-to-machine or IoT protocols. These technological capabilities are an important part of a larger connected future, and customers will begin to expect these types of connected services more often moving forward.

Connected Vehicles Will Completely Transform Transportation

Imagine having vehicles that could communicate with each other and eliminate a crash from happening. Then imagine a driver able to navigate an impending pothole because of their vehicle’s sensors, saving them from a costly repair. Imagine a vehicle that can automatically navigate you to the best parking, saving on gas and time spent. Finally, imagine vehicles and infrastructure that can communicate to optimize traffic routes, avoiding congestion and improving commute times. The other day while I was frantically trying to get to work for an early meeting with one of my bosses, there was a traffic accident on the highway. My navigation system rerouted me seamlessly to another route and I was able to get to my meeting on time.

This automotive technology is a game changer for a better future. The impact on road trips and daily commutes alone is enough to excite. So much potential to create so much. I have been on the Internet since 1995, at the forefront of transitioning print publications to online publications. Also, I never thought that one day, vehicles, infrastructure, and buildings would all be able to communicate and connect. I never realized that what we were doing back in 1995 that seemed so monumental was really quite primitive and just the beginning.  Funny, because something tells me we are still at the beginning and so much great stuff is right around the corner. This is from a guy that is still gushing over wireless Apple car play in my new Ford Edge.

Moving Forward

Nearly two decades later, I’m building strategic positions based on automotive innovation like connected vehicles. I am looking forward to helping OEMs navigate automotive connectivity and help position them as leaders in this space.  There is so much to do and OEMs will need to adapt, transition and leverage the new normal as they truly extend their great manufacturing companies to mobility.

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Tap into Perficient’s automotive expertise to become a leader in connected vehicles.

Introduction

Edge computing and more generally the rise of Industry 4.0 delivers tremendous value for your business. Having the right data strategy is critical to get access to the right information at the right time and place. Processing data on-site allows you to react to events near real-time and propagating that data to every part of your organization will open a whole new world of capabilities and boost innovation.

Today we want the edge to be an extension of the cloud, we’re looking for consistency across environments and containers are at the center of this revolution. It would take way too long to do a comprehensive review of all available solutions, so in this first part, I’m just going to focus on AWS, Azure – as the leading cloud providers – as well as hybrid-cloud approaches using Kubernetes.

Solution Overview

At the core of Industry 4.0 is the collection of equipment and devices data and dissemination of said data to local sites as well as the rest of the organization. The basic flow of data can be summarize like so:

1. Events are emitted by IoT devices over OPC-UA or MQTT to a local broker
2. Part of the raw data is consumed directly for real-time processing (anomaly detection, RT dashboards, etc)
3. Part of the data is (selectively) copied to a message broker for event-driven services, streaming analytics
4. Messages are also (selectively) transferred to the cloud for analytics and global integration
5. Configuration can also be pushed backed to the sites post-analysis

Industrial IoT (IIoT) solution overview diagram

Data Flow

Data Collection

Looking at the edge-most side of our diagram (top in light green), the first step in the solution is to collect the data from the devices. OPC-UA is very typical for industrial equipment, and the historical way we’ve been collecting events on the factory floor. The second, more modern option is MQTT, now available on most IoT devices and certain industrial equipments. Both are IoT optimized transport protocols like HTTP. OPC-UA also specifies a standard data structure for equipment information, while Sparkplug is the standard data structure specification for MQTT.

Most plants will have a mix of both, with older equipment connecting to an OPC-UA server that is bridged to an MQTT broker

OPC-UA MQTT Bridge – Source: Inductive Automation

AWS

AWS IoT Sitewise Edge provides an MQTT gateway and has out-of-the-box support for OPC-UA to MQTT transformation. AWS Sitewise Edge is great to monitor devices on location, and run/visualize simple analytics. Sitewise Edge gateway then copies the data to the cloud where it can be processed by AWS IoT Core, and bridged to other systems. Downstream systems can be AWS IoT services, other AWS services like Kinesis, S3, Quicksight, etc. or non-AWS products like Kafka, Spark, EMR, Elasticsearch, and so on. Sitewise Edge is a software product which can be deployed on AWS outpost which we’re going to discuss later, or existing infrastructure, bare-metal or virtualized environment.

AWS Sitewise Edge – Source: AWS

Azure

Azure IoT Edge edge is the equivalent of AWS Sitewise for Microsoft. IoT Edge ties directly into Azure Iot Hub to make the data available in Azure cloud, which can then be processed using the whole gamut of Azure services like Stream Analytics, Functions, Event Hub, etc

Azure IoT Edge – Source: Azure

Self-Managed

You can also run your own OPC-UA & MQTT broker at the edge, in one of the compute options we’ll discuss down below, but you will be responsible for transferring that data to the cloud. RedHat AMQ, Eclipse Mosquitto, HiveMQ are common MQTT brokers with various degrees of sophistication. Red Hat Fuse, part of the Red Hat Integration suite, can also be used to set up an OPC-UA server if you’re not already using an off-the-shelf solution like Inductive Automation’s Ignition.

This is a great option if you’re just getting started and want to quickly prototype, since they all have trial versions, and/or are just plain free, open-source solutions. HiveMQ and Mosquitto are pure MQTT, while Red Hat Integration’s MQTT implementation is more raw, but offers a much broader range of capabilities beyond MQTT. You can’t go wrong with that option, it will scale really well, you’ll have a lot more flexibility, no vendor lock-in, but there is some assembly required.

Self-managed MQTT/Kafka Stack – Source: RedHat

Streaming Data

In order to process the data for analytics, error detection, ML in general, etc we need to move it into a more suitable messaging system. The most common solution for that kind of workload is Kafka, and most analytics tools already know how to consume data from it. Kafka also supports replication between sites so it’s a great option to move data between sites and to the cloud.

If you’re using Sitewise edge or Azure Edge and you don’t need Kafka on the edge, the MQTT data will automatically be transmitted for you to the cloud (AWS IoT Core & Azure IoT Hub). You can then send that data your cloud hosted Kafka cluster if so desired (and you definitely should).

If you’re running your own MQTT broker, you can use MQTT replication to the cloud in some instances (Mosquitto Mirroring, HiveMQ Replication), but a better option is to use Kafka and leverage the mirroring feature.

Kafka implementations are plenty, RedHat AMQ Streams, part of the RedHat Integration suite, Strimzi for Kubernetes and Confluent Kafka are the most recognized vendors. Neither AWS nor Azure have managed Kafka products at the edge, but have other – native – ways to run analytics (Kinesis, Event Hub, etc), but more on that later.

Compute Options

Next we need to run workloads at the edge to process the data. Again we’ll have 3 options for the infrastructure setup, and many options to deploy applications to that infrastructure.

AWS

If you don’t have an existing compute infrastructure at the edge or if you’re trying to extend your existing AWS footprint to edge locations, the easier way is definitely AWS Outpost. Outpost are physical AWS servers that you run at your location, which come pre-configure with AWS services similar to the ones running in the AWS cloud, and seamlessly integrate with your existing AWS Cloud. Think of it as a private region with some limitations.

Edge Deployment with AWS Outpost – Source: AWS

Sitewise Edge can be deployed directly on Outpost servers as a turnkey solution for basic analytics on location. You can pair it with Wavelength for sites without existing internet connection, going over 5G networks.

AWS Snowball Edge is another hardware option more suitable for rough environments, remote sites without connection when you want to process the data locally and eventually move the data physically into the cloud (and I mean physically, as in sending the device back to AWS so they can copy the storage)

Outpost can locally run AWS services like S3, ECS, EKS, RDS, Elasticache, EMR, EBS volumes and more

You can also run AWS IoT Greengrass on both devices and use it to run Lambda functions and Kinesis Firehose.

This is a cool article about running Confluent Kafka on Snowball devices: https://www.confluent.io/blog/deploy-kafka-on-edge-with-confluent-on-aws-snowball/

Azure

Stack Edge is the Azure counterpart to AWS Outpost, with the mini-series for use cases similar to AWS Snowball. Again, here, seamless integration with your existing Azure cloud. Azure Stack Hub can run Azure services locally, essentially creating an Azure region at your site.

IoT Edge is the runtime, similar to AWS Greengrass, with IoT specific features. Azure services like Azure Functions, Azure Stream Analytics, and Azure Machine Learning can all be run on-premises via Azure IoT Edge.

Kubernetes (on bare-metal or vms)

Of course both options above are great if you’re already familiar and/or committed to a cloud provider and using the cloud provider’s native services. If you’re not, the ramp-up time can be a little intimidating, and even as a seasoned AWS architect, making sense of how to setup all the components at the edge is not straight forward.

An easier first step at the edge, whether you have existing compute infrastructure or not, is to use your own servers and deploy Kubernetes. If you’re already familiar with Kubernetes it’s of course a lot easier. If you’re starting from scratch, with no prior knowledge of Kubernetes or cloud providers’ edge solutions, I’m honestly not sure which one would be quicker to implement.

For Kubernetes, Red Hat Openshift is a great option. Red Hat suite of products has pretty much everything you need to build a solid edge solution in just a few clicks, through the OperatorHub. Red Hat integration provides MQTT, Kafka, runtimes for your message processing microservices and Open Data Hub for AI/ML. Red Hat published a blueprint for industrial edge to get you started: https://redhat-gitops-patterns.io/industrial-edge/

Edge IIoT on Kubernetes

All 3 options have the ability to run Kubernetes at the edge: AWS EKS, Azure AKS or plain Kubernetes (which I don’t recommend), or Openshift (best). A big advantage of using Openshift is the consistent experience and processes across all environments, including multi-cloud. GitOps is a very easy and powerful way to manage large number of clusters at scale and Red Hat Advanced Cluster Manager can be use to further enhance that experience.

Consider the complexity of keeping sites in sync when using AWS or Azure native services at the edge, in terms of applications deployment, architecture changes, etc. at scale. ARM and Cloudformation are available at the edge but you’re not likely to be able to re-use your existing CI/CD process. This is not the case for Kubernetes though, edge and cloud clusters are treated exactly the same way thanks to GitOps.

If you go with Openshift, the integration to the cloud is not seamless. AWS ROSA and Azure ARO are not currently supported on Outpost and Stack Edge so you’re responsible for setting up the cluster, securing the connection to the cloud (VPN) and replicating the data (Kafka Mirroring) to the cloud… so, as always, trade-offs have to be considered carefully.

Conclusion

There is no shortage of options when it comes to implementing edge solutions. All the major cloud providers cover most standard needs, end-to-end data pipelines with native services, even pre-configured server racks that you can just drop into your existing infrastructure. These allow you to easily extend your existing cloud architecture in physical locations. You can also bring your own hardware and software. Red Hat Integration running on Openshift, or the recently release Microshift running on edge optimized Linux is a very powerful and cost effective solution. There is no right or wrong choice here, you just have to consider the effort, cost & timing and find the solution with the best ROI.

Stay tuned for the next part in this series in which we’ll run through the Red Hat IIoT demo and look at what else we can build on top of that foundation.