The Internet of Things (IoT) involves an entire ecosystem of tools and services that must come together to deliver a complete solution. Knowing the key components of an IoT architecture and how to integrate them can be a challenge. Fortunately for you, representative architectures for specific IoT use cases have emerged over the last few years. You can look to these for inspiration when it comes to designing an IoT architecture to meet your own requirements.


Regardless of use case, nearly every IoT solution involves the same four components: devices, connectivity, platform, and an application. Some use cases may involve additional layers, but these four components represent the foundation of every IoT solution.


IoT devices make up the physical hardware component of your solution. In an Industrial Equipment Monitoring use case, these are things like engines and engine controllers. For Smart Environment use cases, these could be motion sensors or badge readers. For Asset Tracking use cases, these are GPS trackers.

In many industrial IoT and smart building use cases, customers prefer to use off-the-shelf devices that can be added to an existing environment or piece of equipment. One of the challenges when choosing off-the-shelf hardware can be gaining access to the data. Many vendors provide siloed solutions, which may work well to solve very specific problems, but don’t work well when you’d like to utilize that data as part of a broader IoT application. When investigating hardware solutions, make sure you can gain access to the data through local protocols like Modbus, Serial, or OPC UA. Some vendors may also have a cloud service where you can access the data through an API.


In most IoT solutions, devices are sending state data to and receiving commands from a centralized IoT Platform. There are a lot of options for how that device-to-platform connection is made and it depends heavily on the environment and constraints of the device itself. If the device is outside and moving around, like in asset tracking use cases, cellular connectivity is a good choice. If the device is indoors in a home or building environment, you may have Ethernet or WiFi available. If the device is battery powered, you may need to investigate low-power options like Bluetooth Low Energy or LPWAN.

Below is a table from our guide, Business Innovation and Expansion with Industrial IoT, that can help you determine the available connectivity options based on your environment and device constraints.


Some devices can’t connect directly to the central platform and require the use of an IoT gateway to bridge the gap between your local environment and your platform. This is common in industrial environments where you may be interfacing with existing equipment over local protocols like Modbus, OPC UA, or Serial. Gateways are also required when using wireless technologies like BLE and LPWAN, since those don’t provide any direct connection to your network or the Cloud.

In these situations, the device is connected to the gateway. The gateway reads the required information and then sends the data to the platform using a “backhaul” connection, like cellular or WiFi, which can access your network or the Cloud.

Gateways also allow you to introduce Edge Compute into your architecture. Edge Compute shifts processing and control from the Cloud and places it at or near your equipment. The Cloud is an important component of your architecture, but it comes with limitations outside of your control, like internet connection reliability and communication latency. If decisions need to be made in real time, or your devices generate too much data to send to the Cloud, introducing Edge Compute into your IoT architecture could be a good solution.


Your IoT Platform is the central data warehouse and orchestration engine for your solution. Building a secure and scalable platform is not an easy task, so we recommend choosing a partner to provide this component of the IoT architecture for you. Choosing the right platform can be a complicated process. Below is the platform evaluation checklist that can be found in our guide, IoT Implementation: From Concept to Production.

  • Industry knowledge
  • IoT knowledge
  • Quality and level of support available
  • Limits on devices, payloads, or data
  • Stability
  • Functionality meets use case needs
  • Security
  • High availability / disaster recovery
  • Continuing education
  • Documentation


IoT platforms are complicated enough that they have their own architecture requirements in order to fulfill the needs of your IoT solution. Understanding a well-designed platform can help you when choosing a partner.

The above diagram shows the architecture for the Losant Enterprise IoT Platform. This diagram shows the primary components you should look for when investigating a platform. These include Edge Compute, Data Ingestion Services, Data Warehousing, Workflows or Rules Engines, Dashboards, and End-User Experiences. The green boxes at the top represent your specific IoT applications. A well-designed platform can enable the creation of many different applications that your organization may be pursuing.


The IoT application delivers the end-user experience, or how you or your customers engage with the data collected from your IoT devices. This could be a mobile app, a website, a desktop application, or even a passive experience that no one interacts with directly. Building these can be challenging and time-consuming. When you’re investigating IoT platforms, look specifically for application enablement platforms, since they provide tools that can greatly accelerate that effort.

The IoT application is an important component of your IoT architecture and is where the actual value of your solution is realized. Deploying hardware and collecting sensor data is meaningless unless you’re presenting it in useful ways and solving real-world problems for your customers.


IoT solutions require a very different architecture that many companies may not be comfortable with. As companies move forward with their digital transformation strategies, understanding this architecture is important in order to be successful. Some companies, like industrial OEMs, sell millions of devices to customers distributed all over the globe. Building a reliable, secure, and scalable application with a highly-distributed system like this requires a strong foundation in order to deliver an exceptional user experience to their customers.

As you move forward with your IoT ambitions, remember these components. Each one represents a partner you’ll likely work with in order to build the complete solution. At Losant, we’ve provided the IoT platform for many customers, big and small, across a wide range of use cases. If you’re investigating platforms, we’d love to chat about your solution and see how we could help build the foundation for your IoT architecture.

reference: losant


With the growing adoption of the Internet of Things (IoT), connected devices have penetrated every aspect of our life, from health and fitness, home automation, automotive and logistics, to smart cities and industrial IoT.

Thus, it is only logical that IoT, connected devices, and automation would find its application in agriculture, and as such, tremendously improve nearly every facet of it. How could one still rely on horses and plows when self-driving cars and virtual reality are no longer a sci-fi fantasy but an everyday occurrence?

Farming has seen a number of technological transformations in the last decades, becoming more industrialized and technology-driven. By using various smart agriculture gadgets, farmers have gained better control over the process of raising livestock and growing crops, making it more predictable and improving its efficiency.

This, along with the growing consumer demand for agriculture products, has contributed to the increased proliferation of smart farming technologies worldwide. In 2020, the market share for IoT in agriculture reached $5.6 billion.

In this article, we will explore the IoT use cases in agriculture and examine their benefits. So, if you are considering investing into smart farming, or are planning to build an IoT solution for agriculture, dive right in.

What is smart agriculture? The definition and market size

There are many ways to refer to modern agriculture. For example, AgriTech refers to the application of technology in agriculture in general.

Smart agriculture, on the other hand, is mostly used to denote the application of IoT solutions in agriculture. So what is smart agriculture using IoT? By using IoT sensors to collect environmental and machine metrics, farmers can make informed decisions, and improve just about every aspect of their work – from livestock to crop farming.

For example, by using smart agriculture sensors to monitor the state of crops, farmers can define exactly how many pesticides and fertilizers they have to use to reach optimal efficiency. The same applies to the smart farming definition.


Although smart agriculture IoT, as well as industrial IoT in general, aren’t as popular as consumer connected devices; yet the market is still very dynamic. The adoption of IoT solutions for agriculture is constantly growing. Namely, COVID-19 has had a positive impact on IoT in the agriculture market share. Disruptions in the supply chain, and the shortage of qualified workers, has propelled its CAGR to 9,9%. In fact, as per recent reports, the smart framing market share is set to reach $6.2 billion by 2021.

At the same time, the global smart agriculture market size is expected to triple by 2025, reaching $15.3 billion (compared to being slightly over $5 billion back in 2016).

Because the market is still developing, there is still ample opportunity for businesses willing to join in. Building IoT products for agriculture within the coming years can set you apart as an early adopter, and as such, help you pave the way to success.

But why should you consider building an IoT application for agriculture in the first place?

The Benefits of smart farming: How’s IoT shaping agriculture

Technologies and IoT have the potential to transform agriculture in many aspects. Namely, there are 5 ways IoT can improve agriculture:

  • Data, tons of data, collected by smart agriculture sensors, e.g. weather conditions, soil quality, crop’s growth progress or cattle’s health. This data can be used to track the state of your business in general as well as staff performance, equipment efficiency, etc.
  • Better control over the internal processes and, as a result, lower production risks. The ability to foresee the output of your production allows you to plan for better product distribution. If you know exactly how much crops you are going to harvest, you can make sure your product won’t lie around unsold.
  • Cost management and waste reduction thanks to the increased control over the production. Being able to see any anomalies in the crop growth or livestock health, you will be able to mitigate the risks of losing your yield.
  • Increased business efficiency through process automation. By using smart devices, you can automate multiple processes across your production cycle, e.g. irrigation, fertilizing, or pest control.
  • Enhanced product quality and volumes. Achieve better control over the production process and maintain higher standards of crop quality and growth capacity through automation.

As a result, all of these factors can eventually lead to higher revenue.

Now that we have outlined how IoT can be advantageously applied in the sphere of agriculture, let’s take a look at how the listed benefits can find their application in real life.

IoT use cases in agriculture (with examples)

There are many types of IoT sensors for agriculture as well as IoT applications in agriculture in general:

1.Monitoring of climate conditions

Probably the most popular smart agriculture gadgets are weather stations, combining various smart farming sensors. Located across the field, they collect various data from the environment and send it to the cloud. The provided measurements can be used to map the climate conditions, choose the appropriate crops, and take the required measures to improve their capacity (i.e. precision farming).

Some examples of such agriculture IoT devices are allMETEOSmart Elements, and Pycno.


2. Greenhouse automation

Typically, farmers use manual intervention to control the greenhouse environment. The use of IoT sensors enables them to get accurate real-time information on greenhouse conditions such as lighting, temperature, soil condition, and humidity.

In addition to sourcing environmental data, weather stations can automatically adjust the conditions to match the given parameters. Specifically, greenhouse automation systems use a similar principle.

For instance, Farmapp and Growlink are also IoT agriculture products offering such capabilities among others.

GreenIQ is also an interesting product that uses smart agriculture sensors. It is a smart sprinklers controller that allows you to manage your irrigation and lighting systems remotely.


3. Crop management

One more type of IoT product in agriculture and another element of precision farming are crop management devices. Just like weather stations, they should be placed in the field to collect data specific to crop farming; from temperature and precipitation to leaf water potential and overall crop health.

Thus, you can monitor your crop growth and any anomalies to effectively prevent any diseases or infestations that can harm your yield. Arable and Semios can serve as good representations of how this use case can be applied in real life.


4. Cattle monitoring and management

Just like crop monitoring, there are IoT agriculture sensors that can be attached to the animals on a farm to monitor their health and log performance. Livestock tracking and monitoring help collect data on stock health, well-being, and physical location.

For example, such sensors can identify sick animals so that farmers can separate them from the herd and avoid contamination. Using drones for real-time cattle tracking also helps farmers reduce staffing expenses. This works similarly to IoT devices for petcare.

For example, SCR by Allflex and Cowlar use smart agriculture sensors (collar tags) to deliver temperature, health, activity, and nutrition insights on each individual cow as well as collective information about the herd.


5. Precision farming

Also known as precision agriculture, precision farming is all about efficiency and making accurate data-driven decisions. It’s also one of the most widespread and effective applications of IoT in agriculture.

By using IoT sensors, farmers can collect a vast array of metrics on every facet of the field microclimate and ecosystem: lighting, temperature, soil condition, humidity, CO2 levels, and pest infections. This data enables farmers to estimate optimal amounts of water, fertilizers, and pesticides that their crops need, reduce expenses, and raise better and healthier crops.

For example, CropX builds IoT soil sensors that measure soil moisture, temperature, and electric conductivity enabling farmers to approach each crop’s unique needs individually. Combined with geospatial data, this technology helps create precise soil maps for each field. Mothive offers similar services, helping farmers reduce waste, improve yields, and increase farm sustainability.

6. Agricultural drones

Perhaps one of the most promising agritech advancements is the use of agricultural drones in smart farming. Also known as UAVs (unmanned aerial vehicles), drones are better equipped than airplanes and satellites to collect agricultural data. Apart from surveillance capabilities, drones can also perform a vast number of tasks that previously required human labor: planting crops, fighting pests and infections, agriculture spraying, crop monitoring, etc.

Read more: Why Use Agriculture Drones? Main Benefits and Best Practices

DroneSeed, for example, builds drones for planting trees in deforested areas. The use of such drones is 6 times more effective than human labor. A Sense Fly agriculture drone eBee SQ uses multispectral image analyses to estimate the health of crops and comes at an affordable price.


7. Predictive analytics for smart farming

Precision agriculture and predictive data analytics go hand in hand. While IoT and smart sensor technology are a goldmine for highly relevant real-time data, the use of data analytics helps farmers make sense of it and come up with important predictions: crop harvesting time, the risks of diseases and infestations, yield volume, etc. Data analytics tools help make farming, which is inherently highly dependent on weather conditions, more manageable, and predictable.

For example, the Crop Performance platform helps farmers access the volume and quality of yields in advance, as well as their vulnerability to unfavorable weather conditions, such as floods and drought. It also enables farmers to optimize the supply of water and nutrients for each crop and even select yield traits to improve quality.

Applied in agriculture, solutions like SoilScout enable farmers to save up to 50% irrigation water, reduce the loss of fertilizers caused by overwatering, and deliver actionable insights regardless of season or weather conditions.

8. End-to-end farm management systems

A more complex approach to IoT products in agriculture can be represented by the so-called farm productivity management systems. They usually include a number of agriculture IoT devices and sensors, installed on the premises as well as a powerful dashboard with analytical capabilities and in-built accounting/reporting features.

This offers remote farm monitoring capabilities and allows you to streamline most of the business operations. Similar solutions are represented by FarmLogs and Cropio.

In addition to the listed IoT agriculture use cases, some prominent opportunities include vehicle tracking (or even automation), storage management, logistics, etc.


Things to consider before developing your smart farming solution

As we can see, the use cases for IoT in agriculture are endless. There are many ways smart devices can help you increase your farm’s performance and revenue. However, agriculture IoT apps development is no easy task. There are certain challenges you need to be aware of if you are considering investing into smart farming.

1. The hardware

To build an IoT solution for agriculture, you need to choose the sensors for your device (or create a custom one). Your choice will depend on the types of information you want to collect and the purpose of your solution in general. In any case, the quality of your sensors is crucial to the success of your product: it will depend on the accuracy of the collected data and its reliability.

2. The brain

Data analytics should be at the core of every smart agriculture solution. The collected data itself will be of little help if you cannot make sense of it. Thus, you need to have powerful data analytics capabilities and apply predictive algorithms and machine learning in order to obtain actionable insights based on the collected data.

3. The maintenance

Maintenance of your hardware is a challenge that is of primary importance for IoT products in agriculture, as the sensors are typically used in the field and can be easily damaged. Thus, you need to make sure your hardware is durable and easy to maintain. Otherwise you will need to replace your sensors more often than you would like.

4. The mobility

Smart farming applications should be tailored for use in the field. A business owner or farm manager should be able to access the information on site or remotely via a smartphone or desktop computer.

Plus, each connected device should be autonomous and have enough wireless range to communicate with the other devices and send data to the central server.


5. The infrastructure

To ensure that your smart farming application performs well (and to make sure it can handle the data load), you need a solid internal infrastructure.

Furthermore, your internal systems have to be secure. Failing to properly secure your system only increases the likeliness of someone breaking into it, stealing your data or even taking control of your autonomous tractors.

6. Connectivity

The need to transmit data between many agricultural facilities still poses a challenge for the adoption of smart farming. Needless to say, the connection between these facilities should be reliable enough to withstand bad weather conditions and to ensure non-disruptive operations. Today, IoT devices still use varying connection protocols, although the efforts to develop unified standards in this area are currently underway. The advent of 5G and technologies like space-based Internet will, hopefully, help find a solution to this problem.

7. Data collection frequency

Because of the high variety of data types in the agricultural industry, ensuring the optimal data collection frequency can be problematic. The data from field-based, aerial and environmental sensors, apps, machinery, and equipment, as well as processed analytical data, can be a subject of restriction and regulations. Today, the safe and timely delivery, and sharing of this data is one of the current smart farming challenges.

8. Data security in the agriculture industry

Precision agriculture and IoT technology imply working with large sets of data, which increases the number of potential security loopholes that perpetrators can use for data theft and hacking attacks. Unfortunately, data security in agriculture is still, to a large extent, an unfamiliar concept. Many farms, for example, use drones that transmit data to farm machinery. This machinery connects to the Internet but has little to zero security protection, such as user passwords or remote access authentications.

Some of the basic IoT security recommendations include monitoring data traffic, using encryption methods to protect sensitive data, leveraging AI-based security tools to detect traces of suspicious activity in real-time, and storing data in the blockchain to ensure its integrity. To fully benefit from IoT, farmers will have to get familiar with the data security concept, set up internal security policies, and adhere to them.

reference: easternpeak

5 IoT Use Cases That Will Shape the Future of Agriculture

Agriculture is changing rapidly, and the Internet of Things (IoT) seeks to potentially disrupt the way we produce and deliver food to the millions of people that’ll be affected by worrying problems such as droughts, fires, natural disasters, and other issues linked to global warming.

Gadgets, health care, manufacturing; these are all areas that IoT has touched in one way or another, but is it possible for the smart farming industry to keep up with the Internet of Things, or will the technologies used in agriculture be inadequate for a true, one-to-one connection?

In this article, we’re going to explore five IoT use cases that will shape the future of agriculture. But before we do so, it’s important to understand how IoT is used in agriculture, and whether or not the smart farming industry is reacting to the constant innovations quickly enough.

How is the Internet of Things Used in Agriculture?

Regardless of your familiarity with the industry, you’ve likely heard of smart farming. It’s a buzzworthy topic that is currently surging in popularity. A broad definition of smart farming is the use of technology to improve farming efforts (i.e. making the farmers’ lives easier).

Smart farming offers awareness to growers who wish to steer clear of issues and intervene before small (or big!) problems affect profits. The Internet of Things comes into play via the connected devices that tell farmers what they need to know regarding soil, humidity, water levels, and other important metrics.

Even the government is starting to embrace new opportunities in smart farming. The United States Department of Agriculture (USDA) recently turned a 7,000-acre farm at its Beltsville Area Research Facility into a testbed for IoT technology and related advancements, such as Artificial Intelligence (AI). This initiative will reportedly help thousands of data scientists collect information faster.

The overall smart farming sector deals with more than IoT tech though. As you’ll see from the following five examples, these advancements are instrumental to the future of farming…

Did you know that Ubidots can help farmers connect the dots between their field data and a more sustainable growth?

Take a peek at how we plan to connect the future of food with Climate Smart Agriculture.LEARN MORE

1. Aid Pest Management

“Inadequate pest management could translate to disappointing, unprofitable growing seasons. Manual methods used by farmers to check for pest infestations are time-consuming. Plus, issues may go unnoticed until it’s already too late.”

IoT sensors can provide real-time information about crop health and clearly show the presence of pests. Low-resolution image sensors are ideal for assessing crops across a large area. These devices capture images of pests the naked eye can’t see.

In contrast, there are high-resolution sensors that capture the amount of light energy released by a plant—also known as a spectral signature.

Farmers pay close attention to factors that make infestations more likely when deciding to implement IoT devices for pest control.

For example, IoT sensors can gather data about general pest behavior patterns on a farm, allowing users to know if prevention methods are sufficient. If and when specific weather patterns make pests more prevalent, IoT sensors can offer predictive analyses to help farmers prepare in advance.

Smart farming devices can inform farmers on whether their current pesticide usage leads to the necessary results or not. When users collect regular, up-to-date information, they can make continual adjustments to how, when and where to apply pest management strategies. This approach allows them to use smart farming strategically instead of hoping for the best outcome.

2. Improving Water Usage

Water is a complex resource in agriculture. Using too much or too little of it can have adverse consequences on crop yields and soil health.

According to one IoT solutions provider, connected sensors could reduce water consumption by 30% while improving land management decisions. The company’s technology measures moisture in the soil. Then, it provides data to help farmers take action against drought or overwatering.

In Southern California, farmers place sensors around avocado trees to measure the water levels. The sensors connect to sprinkler systems that treat the thirsty trees as required. At night, the water shuts off at the right times to avoid waste.

This setup automates significant parts of the process, allowing farmers to stop engaging in numerous manual tasks. Such an advantage is one of the reasons experts cite the Internet of Things in agriculture as one of the most recent breakthroughs in technology, making them curious about what the future holds.

3. Maximize Profitability

Professionals in the agriculture sector have to pay attention to market conditions to maintain a competitive advantage. Some of them use IoT sensors to increase harvests and beat other producers to the market.

“For example, in China’s Shunyi district, a strawberry greenhouse equipped with IoT technology and big data analytics increased production by more than 100%. Plus, it shortened the time to market by nearly three weeks.

The data-gathering system allowed reducing the necessary labor force by 50% per kilogram of strawberries. Although strawberries are not one of China’s top exports, this smart farming example shows how purposeful use of IoT sensors could help streamline processes and compete with other nations.

IoT technology boosts profits by reducing risks. If a farmer installs a sensor on a tractor or piece of equipment, the collected data could send a warning once a part is about to wear out. When farmers ensure maintenance is preventative⁠—not due to incident—farms can avoid costly lapses in operations.

4. Monitor Animals

IoT technology has spurred positive changes in the way farmers keep tabs on grazing animals, such as sheep and cows. It’s now common for many creatures to wear fabric-covered collars that contain tracking capabilities.

IoT technology has spurred positive changes in the way farmers keep tabs on grazing animals, such as sheep and cows. It’s now common for many creatures to wear fabric-covered collars that contain tracking capabilities.

A new initiative in Wales involved using IoT tech at nearly 20 farms. One cattle farmer believes the technologywill reduce the time required to find lost animals.

Plus, it will even show which spots the cows prefer to graze!

The Internet of Things can also give farmers updates on the health of their animals. One company offers a device with a 95% accuracy rate for predicting if a cow is pregnant. The smart farming system, which involves IoT sensors placed into a cow’s throat and stomach, lasts for four years before a replacement is needed. If an animal seems to be visibly sick, it can automatically contact a vet.

In Britain alone, these devices track 15,000 cows. Operations across the world, including the U.S., China and the Middle East, have an eye on the tech. However, with a setup cost of $600 per cow, implementation can be expensive.

5. Become Climate-Proof

People are increasingly focused on how to preserve the planet’s future. Scientists warn that drastic, committed and collective action must occur to avoid climate catastrophe. However, population growth may worsen the effects of climate change and directly impact more individuals.

Researchers continuously wonder how to provide people with access to nutritious food even as the world becomes more populated. Unfortunately though, climate change could wreak havoc by disrupting typical growing seasons.

In part due to this problem, vertical facilities have taken off in the smart farming industry. Many people believe they’ll solve numerous food crises associated with climate change. For example, a vertical farm can have 12 growing cycles per year instead of just a few. These are indoor farms, so they don’t need soil or natural light to thrive.

The operators of vertical farms can grow more fruits and vegetables when compared to a conventional setup. Plus, they do so in tightly controlled environments centered around feedback provided by smart IoT sensors.

Vertical farms work well for urban environments because they make use of abandoned spaces such as warehouses and former parking garages.

Conventional farming is impractical in densely populated cities because there” not enough space for crops to flourish. As a result, the carbon emissions associated with transporting produce to those who need it increase, which is bad news for both the planet and, ultimately, us.

Thanks to the rise of vertical farming, agriculture could someday become a fixture in many cities, and people could easily access healthy sustenance. The indoor setups can offer prosperous harvests year-round, even if climate change causes non-ideal weather patterns.

reference: ubidots

What is IoT architecture?

The concept behind the Internet of Things is as powerful as it is complex, and in order for the elements in the IoT puzzle to mesh together perfectly, they all have to be part of a well-thought-out structure. This is where IoT architecture enters the stage, especially in terms of IoT device management.

From IoT hype to IoT reality

The first thing that comes to the mind of an average John Doe when hearing the catchphrase ‘Internet of Things’ is probably a smart coffee maker that knows exactly what kind of coffee he will need in the morning before he even wakes up and realises it. Or, better still, a futuristic-looking autonomous car dashing through the IoT-empowered streets without the ‘driver’ even touching the steering wheel once.

While these hopeful-but-naïve visions are not as far-fetched from reality as they sound, IoT is not only about home and urban automation. In fact, far from being a mere buzzword, it stands for many, many more. Indeed, just as the Internet of Things has the power to change and improve our daily lives along with the ways in which we function as a society, it can also transform the way business is run and, ultimately, the way we perceive practically every aspect of our world.

Why do you need a robust Internet of Things architecture?

Still, when talking about the Internet of Things, much attention is paid to its potential. News about what IoT will be able to do and how it will empower our lives keeps flooding in, but for many it may seem that these uplifting visions don’t translate into reality as fast as we wish they could. Nevertheless, the big change does happen, yet it happens in dribs and drabs rather than in giant leaps. The reason for this is quite simple, but it tends to stay out of the public eye: it is the inherent diversity of IoT systems that stifles the progress and often stands in the way to make all things connected.

Why do you need robust Internet of Things architecture?

As one of two presumably biggest challenges standing before IoT (the other being security), fragmentation is at the core of the Internet of Things because of the diverse nature of the Things that it aims to connect. Putting any IoT system to work requires harnessing all the resources, hardware, software, and systems, however varied they all may be, into one single framework to form an integrated, reliable, and cost-effective solution. In simple terms, every IoT deployment needs a rock-solid IoT architecture to be able to serve its designed purpose; the resulting efficiency and applicability of the system largely depends on the quality of the infrastructure developed.

IoT architecture building blocks

While every IoT system is different, the foundation for each Internet of Things architecture as well as its general data process flow is roughly the same. First of all, it consists of the Things, which are objects connected to the Internet which by means of their embedded sensors and actuators are able to sense the environment around them and gather information that is then passed on to IoT gateways. The next stage consists of IoT data acquisition systems and gateways that collect the great mass of unprocessed data, convert it into digital streams, filter and pre-process it so that it is ready for analysis. The third layer is represented by edge devices responsible for further processing and enhanced analysis of data. This layer is also where visualisation and machine learning technologies may step in. After that, the data is transferred to data centres which can be either cloud-based or installed locally. This is where the data is stored, managed and analysed in depth for actionable insights.

These are the four layers of IoT architecture described in detail:

3 Layers of IoT architecture

Things, sensors and controllers

As the basis for every IoT system, connected devices are responsible for providing the essence of the Internet of Things which is the data. To pick up physical parameters in the outside world or within the object itself, they need sensors. These can be either embedded in the devices themselves or implemented as standalone objects to measure and collect telemetry data. For an example, think of agricultural sensors whose task is to measure parameters such as air and soil temperature and humidity, soil pH levels or crop exposure to sunlight.

Another indispensable element of this layer are the actuators. Being in close collaboration with the sensors, they can transform the data generated by smart objects into physical action. Let’s imagine a smart watering system with all the necessary sensors in place. Based on the input provided by the sensors, the system analyses the situation in real time and commands the actuators to open selected water valves located in places where soil humidity is below the set value. The valves are kept open until the sensors report that the values are restored to default. Obviously, all of this happens without a single human intervention.

What is also important is that the connected objects should not only be capable of communicating bidirectionally with their corresponding gateways or data acquisition systems, but also being able to recognise and talk to each other to gather and share information and collaborate in real time to leverage the value of the whole deployment. In case of resource-constrained and battery-operated devices particularly, achieving this is not an easy task since such communication requires lots of computing power and consumes precious energy and bandwidth. Therefore, a robust architecture can only enable effective device management when it uses fit-for-purpose, secure and lightweight communication protocols, such as Lightweight M2M which has become a leading standard protocol for the management of low power lightweight devices which are typical for many IoT use cases

Things, sensors and controllers

Gateways and data acquisition

Although this layer still functions in close proximity with sensors and actuators on given devices, it is essential to describe it as a separate IoT architecture stage as it is crucial for the processes of data collection, filtering and transfer to edge infrastructure and cloud-based platforms. Given the massive volume of input and output that million-device deployments may generate, capabilities for the aggregation, selection and transportation of data should be in the spotlight. As intermediaries between the connected things and the cloud and analytics, gateways and data acquisition systems provide the necessary connection point that ties the remaining layers together.

Sitting at the verge of the worlds of OT and IT, gateways facilitate communication between the sensors and the rest of the system by converting the sensor data into formats that are easily transferable and usable for other system components down the line. What’s more, they are able to control, filter and select data to minimise the volume of information that needs to be forwarded to the cloud, which positively affects network transmission costs and response times. Thus, gateways provide a place for the local preprocessing of sensor data which is squeezed into useful bundles ready for further processing.

Another aspect that the gateways support is security. Because the gateways are responsible for managing the information flow in both directions, with the help of proper encryption and security tools they can prevent IoT cloud data leaks as well as reduce the risk of malicious outside attacks on IoT devices.

Gateways and data acquisition

Edge analytics

While not being an inevitable component of every IoT architecture, edge devices can bring significant benefits especially to large-scale IoT projects. In the face of limited accessibility and data transfer speed of the IoT cloud platforms, edge systems can provide quicker response times and more flexibility in the processing and analysis of IoT data. As speed of data analysis is key in some Industrial Internet of Things applications, edge computing has recently seen a dramatic increase in popularity among Industrial Internet of Things ecosystems.

As edge infrastructure can be located closer to the data source in physical terms, it is easier and quicker for it to act on the IoT material in real time and provide output in the form of instant actionable intelligence. In this scenario, only the larger chunks of data which really need the power of the Cloud to be processed are forwarded there. By minimising network exposure, security can be significantly enhanced, while reduced power and bandwidth consumption contributes to more efficient leveraging of business resources.

Edge analytics
Data centre / Cloud platform

If sensors are neurons and the gateway is the backbone of IoT, then the cloud is the brain in the Internet of Things body. Contrary to edge solutions, a data centre or a cloud-based system is designed to store, process and analyse massive volumes of data for deeper insights using powerful data analytics engines and machine learning mechanisms which edge systems would never be able to support.

Having seen increased adoption (especially in Industrial IoT architecture) over the past several years, cloud computing contributes to higher production rates, reduction of unplanned downtime and energy consumption and many other business benefits.

If furnished with proper user application solutions, the cloud can provide business intelligence and presentation options that help humans interact with the system, control and monitor it and make informed decisions on the basis of reports, dashboards and data viewed in real time.Data centre / Cloud platform

Example Internet of Things architecture

Healthcare is among the major industries that have been leaders and forerunners in the adoption of the Internet of Things technologies. The reason for this is that IoT systems help to leverage high quality care for patients and combine it with long-run but massive savings.

Within healthcare, the key IoT applications include, but are not limited to, enhancement of patient and personnel safety and security, reduction of unnecessary healthcare costs, and the provision of suitable support at the right time by employing IoT-empowered smart medical and emergency systems.

In view of the huge population challenges ahead, one of the greatest concerns in healthcare is elderly care and monitoring of illnesses like diabetes and heart-related diseases. Thus, prevention plays a key role in providing better health for elderly patients. Therefore, it is no wonder that the Internet of Things is gaining ground especially in health monitoring, where reliability, security and real-time precise control are a must.

The example automatic monitoring system for elderly patients requires data collection and real-time analysis, network connectivity for access to the infrastructure services, and an application to support user interface and display. Therefore, its architecture must include body sensors to collect patient data, gateways to filter and forward the data, microcontrollers or microprocessors to analyse and wirelessly send the data to the cloud as well as a communication tool to transfer the data to a remote location like emergency service or healthcare provider for monitoring and tracking purposes.

The IoT architecture for the system consists of three stages: physical, communication, and application. The first layer features a multiple-sensor network that evaluates the patient’s vital readings such as nutrition, medical intakes, and physical activities. Also included in the physical layer is another monitoring network that consists of in-house sensors and actuators to maintain air quality, temperature, and to analyse and determine any hazardous conditions for the patient. The second layer includes OT devices that collect the information gathered by the sensors, translate it into meaningful data streams and transfer them to a back-end destination. The third layer is where data is received, stored, and processed using cloud-based data analysis engines and machine learning mechanisms. The resulting insights can be used to recommend the proper healthcare service for each specific situation or applied in further research or management purposes.

What is IoT architecture?

The healthcare monitoring system presented must provide accessibility to different users. For example, the healthcare provider, the patient themselves, and any family members or caregivers. In view of this, one of the challenges of using IoT within healthcare monitoring is providing data security and privacy. Security can be achieved by having an encryption when transferring the data. An example is the use of a microprocessor that ensures and provides a secure encryption communication method through a secure socket layer (SSL).


As stated previously, IoT architecture may vary from solution to solution, but its core consists of the four building blocks that are key in providing the fundamental features that make a sustainable IoT ecosystem: functionality, scalability, availability, maintainability and cost-effectiveness. What is important here is not to let oneself be overwhelmed by the perceived complexity of the Internet of Things architecture and not to lose sight of the possibilities for implementing attractive and future-proof IoT projects. It is worth noting that a growing focus on the development of a robust IoT architecture observed among many major business players from various industry sectors has led them to success in squeezing more business value from their data to give them a competitive edge and help to outperform their competitors.

While it is true that there are still tons of work to be done in terms of overcoming IoT technology fragmentation, upon looking back, it is quite evident that much effort has been done to date to integrate the vast range of technologies and standards embraced by IoT (examples: LwM2M, oneM2M) and there is hope for a more unified and standardised future. However, before this becomes reality, the key to making the promise of IoT happen doesn’t necessarily lie in obtaining a single rule-them-all IoT technology, but rather putting all the technologies in line so that they are efficient in the collection, management, analysis, and exploitation of the data by building a strong, future-proof, scalable and secure IoT architecture.

reference: avsystem