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4 Questions to Ask Before Adopting the Internet of Things

Saba Anees

The Internet of Things (IoT) is about connecting virtually any “thing” or machine. They could range from personal wearables to smart homes, smart cities’ infrastructure, utilities, transportation, and manufacturing. The IoT is far bigger than the Internet of people, and it’s growing fast. Gartner says the IoT will grow 30 percent in 2016, reaching 6.4 billion devices, with more than five million new devices connected daily. It’s expected to continue growing to 20.8 billion devices by 2020.

You already see the potential of adopting an Internet of Things model into your enterprise, but are you doing it in the best way? The following are four questions you and your team should be answering to determine how to find the right opportunity in the IoT space for your business.

1. What is the Internet of Things?

First things first. Defining the Internet of Things, and establishing its context to your framework is instrumental in determining your potential with IoT. Gartner defines the IoT as “the network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment.” Verizon identifies three characteristics of IoT devices:

■ Aware: The devices include sensors that report information about their surroundings.

■ Autonomous: IoT devices are connected and automatically transfer information to a central location or application for processing.

■ Actionable: The information collected is integrated into business processes for decision making.

2. Is your software configured to connect with the IoT?

Talking about the IoT in terms of things makes it sound like the IoT is all about physical hardware. While the IoT doesn’t exist without sensor-based devices, the devices don’t actually function without software. Most IoT devices have a user interfaced website or smartphone app where the user can manage configuration settings and review activity. Some IoT devices have more sophisticated analytics that gather big data and crunch the numbers to make decisions about what the device should do or present insights to business management.

While building the software that runs on a device may require specialized skills for embedded programming, the backend processes are conventional software applications with common software development concerns, including performance and ease of use. The usual security concerns around software become even more important with the IoT, as software controls devices in the real world and security failures can impact physical systems.

3. Do your team’s technical capabilities scale with the needs of the IoT?

Technology developments now make dealing with the technical challenges of IoT devices easier. Platforms like Raspberry Pi provide low-cost boards equipped for IoT development. Low-power sensors and new low-power communication technology, such as LoRa, mean the limited power available to IoT devices does not limit functionality. Sensors and circuits are shrunk to the point that they fit into devices a person is willing to wear.

On the software side, companies have made platforms to create a standardized environment for IoT development. Applications can use RESTful APIs or lightweight protocol, which were designed to work where memory and network capacity are limited.

Both Amazon Web Services and the Google Cloud Platform offer features explicitly intended to meet the needs of IoT applications, including both real-time communications with IoT devices and performance of the big data analytics necessary to make sense of data once it accumulates. Combined with the hardware platforms, these services make it easy to get started prototyping a device and its software. Because prototyping platforms are scalable, if an idea is not successful, it is easy to continue developing it and create a robust product without throwing away the work that was already done.

4. How does it create a ROI for your business?

Customer-generated data collected by IoT devices offer companies insight into customer behavior and create additional selling opportunities. They provide an in-depth insight that provides opportunity for companies to forecast everything from product roadmaps to market leverage. There are four main kinds of benefits for businesses:

■ Improvements in operational efficiency and asset utilization: Companies gain the ability to manage equipment remotely and schedule preventive maintenance to eliminate downtime. The IoT can also help with optimizing supply chains and loss prevention.

■ An outcome-based business model: The tracking and monitoring enabled by the IoT lets companies change the way they sell equipment. The use of sensors allows them to sell based on usage and quality level, allowing capital goods to adopt the “as-a-Service” model that’s become popular for software.

■ Analytics-based controls: Combining analytics with smart devices will let companies fine-tune control over their processes. Adjustments can be made in real time to ensure continued production and compliance with environmental standards.

■ Improved work efficiency: Smart devices will allow increased collaboration between workers and equipment, improving productivity.

Saba Anees is the Content Marketing Specialist at AppDynamics.

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4 Questions to Ask Before Adopting the Internet of Things

Saba Anees

The Internet of Things (IoT) is about connecting virtually any “thing” or machine. They could range from personal wearables to smart homes, smart cities’ infrastructure, utilities, transportation, and manufacturing. The IoT is far bigger than the Internet of people, and it’s growing fast. Gartner says the IoT will grow 30 percent in 2016, reaching 6.4 billion devices, with more than five million new devices connected daily. It’s expected to continue growing to 20.8 billion devices by 2020.

You already see the potential of adopting an Internet of Things model into your enterprise, but are you doing it in the best way? The following are four questions you and your team should be answering to determine how to find the right opportunity in the IoT space for your business.

1. What is the Internet of Things?

First things first. Defining the Internet of Things, and establishing its context to your framework is instrumental in determining your potential with IoT. Gartner defines the IoT as “the network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment.” Verizon identifies three characteristics of IoT devices:

■ Aware: The devices include sensors that report information about their surroundings.

■ Autonomous: IoT devices are connected and automatically transfer information to a central location or application for processing.

■ Actionable: The information collected is integrated into business processes for decision making.

2. Is your software configured to connect with the IoT?

Talking about the IoT in terms of things makes it sound like the IoT is all about physical hardware. While the IoT doesn’t exist without sensor-based devices, the devices don’t actually function without software. Most IoT devices have a user interfaced website or smartphone app where the user can manage configuration settings and review activity. Some IoT devices have more sophisticated analytics that gather big data and crunch the numbers to make decisions about what the device should do or present insights to business management.

While building the software that runs on a device may require specialized skills for embedded programming, the backend processes are conventional software applications with common software development concerns, including performance and ease of use. The usual security concerns around software become even more important with the IoT, as software controls devices in the real world and security failures can impact physical systems.

3. Do your team’s technical capabilities scale with the needs of the IoT?

Technology developments now make dealing with the technical challenges of IoT devices easier. Platforms like Raspberry Pi provide low-cost boards equipped for IoT development. Low-power sensors and new low-power communication technology, such as LoRa, mean the limited power available to IoT devices does not limit functionality. Sensors and circuits are shrunk to the point that they fit into devices a person is willing to wear.

On the software side, companies have made platforms to create a standardized environment for IoT development. Applications can use RESTful APIs or lightweight protocol, which were designed to work where memory and network capacity are limited.

Both Amazon Web Services and the Google Cloud Platform offer features explicitly intended to meet the needs of IoT applications, including both real-time communications with IoT devices and performance of the big data analytics necessary to make sense of data once it accumulates. Combined with the hardware platforms, these services make it easy to get started prototyping a device and its software. Because prototyping platforms are scalable, if an idea is not successful, it is easy to continue developing it and create a robust product without throwing away the work that was already done.

4. How does it create a ROI for your business?

Customer-generated data collected by IoT devices offer companies insight into customer behavior and create additional selling opportunities. They provide an in-depth insight that provides opportunity for companies to forecast everything from product roadmaps to market leverage. There are four main kinds of benefits for businesses:

■ Improvements in operational efficiency and asset utilization: Companies gain the ability to manage equipment remotely and schedule preventive maintenance to eliminate downtime. The IoT can also help with optimizing supply chains and loss prevention.

■ An outcome-based business model: The tracking and monitoring enabled by the IoT lets companies change the way they sell equipment. The use of sensors allows them to sell based on usage and quality level, allowing capital goods to adopt the “as-a-Service” model that’s become popular for software.

■ Analytics-based controls: Combining analytics with smart devices will let companies fine-tune control over their processes. Adjustments can be made in real time to ensure continued production and compliance with environmental standards.

■ Improved work efficiency: Smart devices will allow increased collaboration between workers and equipment, improving productivity.

Saba Anees is the Content Marketing Specialist at AppDynamics.

Hot Topics

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.