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I am Sanket Shah, founder and CEO of Deuex Solutions, where I focus on building scalable web mobile and data driven software products with a background in software development. I enjoy turning ideas into reliable digital solutions and working with teams to solve real world problems through technology.
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What makes a business suddenly care about connected devices?
Usually, it is not the device itself. It is the moment someone realizes they are losing time, money, visibility, or control because they cannot see what is happening in the real world fast enough.
That is where IoT steps in.
IoT applications connect physical objects to software systems so businesses can monitor, measure, automate, and improve what used to stay hidden. That is the simple version. The more interesting version is what happens after that connection is made.
A machine starts warning you before it fails. A shipment tells you it is delayed before a customer calls. A cold storage unit flags a temperature issue before products are ruined.
That is why this topic keeps growing.
McKinsey estimated that IoT could create up to $11.1 trillion in annual economic value across settings such as factories, cities, homes, retail environments, and health by 2025, with factories and other production environments among the biggest value pools. GSMA Intelligence also notes that the global IoT market is expected to keep growing through 2030, with room for new use cases and business models.
So let’s get practical.
This guide is not about buzzwords. It is about where iot applications create real business value, why some projects work while others stall, and what teams should think about before they build.
An IoT application is a software system that receives data from connected devices, turns that data into useful information, and then triggers action.
That action could be simple.
send an alert
update a dashboard
turn a device on or off
create a service ticket
Or it could be bigger.
predict equipment failure
reroute deliveries
adjust energy usage
automate compliance reporting
In our experience, this is the part many teams miss. They get excited about sensors, connectivity, and dashboards. But the real value comes from the decision layer.
If nothing changes after the data arrives, the system becomes a fancy reporting tool.
And nobody budgets for “fancy reporting tools” for very long.
Because visibility changes behavior.
When teams can see what is happening in real time, they stop reacting late. They stop guessing. They stop overcorrecting.
That matters in manufacturing. It matters in logistics. It matters in healthcare. It even matters in offices and commercial buildings where energy waste quietly eats budgets every month.
Deloitte’s 2025 Smart Manufacturing Survey, based on 600 executives at large manufacturers, found that smart manufacturing and operations are now top priorities because leaders see strategic and operational value in connected systems, data analytics, and cyber security investments.
That line is easy to skim past. It should not be.
Because it tells you something important. IoT is no longer a side experiment. In many sectors, it is moving closer to core operations.
This is the one that gets mentioned most often. There is a reason for that.
It works.
Machines leave clues before they fail. Vibration patterns shift. Temperature rises. Run time changes. Output starts dipping in subtle ways long before a breakdown becomes visible.
IoT applications collect that machine data and compare it against known patterns. The software then tells teams when maintenance is actually needed.
Not too early. Not too late.
When we worked with teams discussing machine monitoring projects, one pattern kept coming up. Maintenance was often scheduled by calendar, not by condition. That sounds safe on paper. In reality, it leads to two expensive outcomes.
healthy equipment gets serviced too often
weak equipment fails between service windows
Predictive maintenance cuts both problems.
Benefits usually include:
reduced downtime
longer equipment life
lower maintenance cost
better spare parts planning
This is one of those use cases that sounds technical until you connect it to the shop floor. Then it becomes obvious.
A stopped machine is not just a machine problem. It is a production problem. A delivery problem. A customer problem.
Here is another question businesses ask late.
Where is the asset right now?
That sounds simple. It rarely is.
In logistics and supply chain environments, companies often lose time searching for pallets, vehicles, containers, tools, or field equipment. Nobody calls it “loss” because the asset still exists. But the waste is real.
IoT applications solve this by combining sensors, GPS, cellular connectivity, RFID, or BLE beacons with software that shows movement and status in real time.
Now the use case gets interesting.
A tracking platform can tell you:
where a shipment is
whether it stayed within temperature limits
whether it was delayed
whether a route change is needed
whether an asset is idle too often
We noticed something in these discussions. Companies usually start by wanting “tracking.” Very quickly, they realize they actually want control.
Tracking is the first step. Operational decisions are the bigger win.
This one matters more than many people realize.
If you transport pharmaceuticals, vaccines, lab samples, fresh food, or any temperature sensitive goods, small fluctuations can ruin product quality. The worst part is not the incident itself. It is discovering the issue too late.
IoT applications solve that by monitoring conditions in real time.
Common data points include:
temperature
humidity
door open events
transit duration
storage conditions
Instead of checking conditions after delivery, teams can respond during transit.
That changes everything.
A system alert sent at the right moment can save an entire shipment. That single intervention can justify the project.
Factories are full of signals. Most of them go unused.
Machines generate data. Production lines generate data. Operators create data. Environmental conditions affect output too. Yet many facilities still rely on fragmented systems and delayed reporting.
This is why manufacturing keeps showing up in serious IoT conversations.
McKinsey identified factories and other process driven production environments as some of the highest value settings for IoT, and Deloitte’s recent smart manufacturing survey shows that executives are actively investing in connected systems to improve agility and performance.
Useful IoT applications in manufacturing include:
machine health monitoring
production line visibility
quality tracking
downtime analysis
worker safety monitoring
environmental condition control
When we worked with a client conversation around industrial systems, one of the biggest surprises was how much time people spent reconciling numbers from different systems. Production said one thing. Maintenance said another. Operations had a third view.
Connected applications do more than show data. They give everyone the same version of what is happening.
That is a much bigger win than most teams expect.
Not every IoT project has to involve factories or fleets.
Some of the most practical use cases happen inside commercial buildings.
Energy costs are rarely driven by one dramatic mistake. They usually come from a hundred small inefficiencies that no one notices day to day.
IoT applications can monitor:
room occupancy
HVAC performance
lighting usage
power consumption
air quality
equipment run time
Then they connect that data to automation rules.
Lights switch off when spaces are empty. Cooling adjusts based on occupancy. Equipment that runs out of schedule gets flagged.
This is where software turns building operations from reactive to intelligent.
And here is the part people find interesting once they see it in action. Smart building IoT is not only about saving energy. It also affects comfort, maintenance planning, and workplace experience.
A building that runs better is cheaper to operate. It is also easier to manage.
Healthcare IoT gets a lot of attention, but not all of it is useful. The flashy examples get headlines. The practical ones create value.
Connected healthcare applications can support:
remote patient monitoring
medication adherence tracking
hospital asset monitoring
connected diagnostics
temperature monitoring for labs and storage
staff and equipment utilization visibility
Why does this matter?
Because healthcare is full of environments where timing matters. Small delays matter. Missing equipment matters. Unseen trends in patient data matter.
In our experience, healthcare teams are often less interested in “smart devices” and more interested in reliability. They want fewer blind spots. Fewer manual checks. Faster escalation.
That is where IoT earns its place.
Retail is changing in quieter ways than people think.
Not every retail IoT application is about futuristic shelves or cashier less stores. Some are far more grounded.
Retailers use connected systems for:
inventory visibility
shelf monitoring
in store traffic analysis
refrigeration monitoring
theft reduction
queue management
A simple example says a lot.
If a refrigerated display unit fails in a store, product loss begins before staff even notice. A connected monitoring system turns that into an instant alert instead of an end of day surprise.
That is the pattern with IoT. It reduces the gap between event and awareness.
And that gap is usually where cost hides.
This is one of the clearest examples of physical reality meeting software.
Agriculture teams deal with weather, soil, water, equipment, and timing. Decisions are physical. But increasingly, they are also data driven.
IoT applications in agriculture can monitor:
soil moisture
weather conditions
irrigation performance
livestock movement
equipment status
storage conditions
This leads to better decisions around watering, feeding, harvesting, and maintenance.
We noticed that many people outside agriculture underestimate how operationally complex it is. Once you start looking at it through a connected systems lens, the use cases multiply fast.
And each one ties directly to yield, quality, or cost.
Mobility is another area where IoT quietly reshapes operations.
Connected vehicle applications can support:
route optimization
driver behavior monitoring
fuel usage analysis
preventive maintenance
safety alerts
usage based insurance models
A vehicle is not just transport anymore. It is also a moving data source.
That changes how businesses manage field teams, service fleets, delivery networks, and even customer experience.
Because once location, condition, and performance data become visible, the backend software can start making smarter calls.
This use case gets less attention than it should.
Safety is often treated as documentation first and visibility second. IoT flips that.
Connected safety applications can monitor:
air quality
gas exposure
worker location
restricted area access
fatigue indicators
environmental hazards
That matters most in industrial, field service, and high risk environments. A real time alert can prevent injury. A pattern of repeated alerts can uncover process problems before something serious happens.
When we looked at industrial use cases, one thing stood out. Safety teams often carry huge responsibility but limited real time information. Connected applications change that balance.
They do not replace human judgment. They support it at the right moment.
This is the question more leaders should ask.
Not every IoT project deserves to be built.
Some fail because the business case is weak. Others fail because the software is disconnected from daily workflows. And some fail because teams collect data without deciding what action should follow.
The strongest projects usually have a few things in common.
Not “digital transformation.”
A real problem.
frequent breakdowns
missing assets
wasted energy
temperature excursions
poor visibility
What happens when the system detects something?
Who gets notified?
What changes automatically?
What decision gets made?
A dashboard is helpful. It is not the outcome.
The outcome is what the team does next.
Bad sensor data leads to bad decisions. Weak connectivity leads to missing events.
This part is less glamorous, but it determines whether the application can be trusted.
The visible part is usually the dashboard or app. The real system is deeper.
Most IoT applications include:
sensors or connected devices
device communication layer
cloud or edge processing
data storage
analytics or rules engine
dashboards, apps, or workflow tools
security controls
That means IoT application development is never only about hardware.
It is also about backend systems, mobile interfaces, alerts, APIs, data pipelines, and security architecture.
Which is why many teams underestimate the effort at the start.
Connected systems increase visibility. They also increase exposure.
Every connected endpoint can become a risk if security is weak.
That does not mean IoT is unsafe. It means security has to be built in from the start.
That includes:
device authentication
encrypted communication
role based access
secure firmware updates
API protection
network segmentation
audit visibility
We noticed that businesses get excited about device rollout and postpone security conversations. That is backwards.
If the application touches operations, security belongs in the first planning discussion.
Start smaller than you want.
That sounds boring. It is usually smart.
Pick a use case where:
the problem is already measurable
the users are easy to identify
the data needed is clear
success can be proven in a few months
Good first projects often involve:
monitoring one equipment class
tracking one asset category
optimizing one facility area
reducing one recurring loss point
That approach builds confidence and gives teams a model they can scale.
They make the invisible visible.
That is the beginning of the value.
After that, the software helps teams react faster, plan better, reduce waste, and run operations with fewer surprises. Sometimes the win is cost reduction. Sometimes it is uptime. Sometimes it is safety. Sometimes it is customer trust.
But it usually starts the same way.
A business realizes it has been operating with blind spots.
And once those blind spots are gone, it does not want to go back.
