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Top 12 Technology Trends In IoT To Watch For In 2024

Coming from our experience with IoT applications and observing our recent projects, we came up with this list of IoT trends to watch in 2024.

WT
Waverley Team
Content Writer
April 29, 202428 min read
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Top 12 Technology Trends In IoT To Watch For In 2024
The Latest IoT Tech Trends

If technology continues at the pace that it is currently at, we can expect to see as many as 28 billion Internet of Things devices that are connected on the Internet by the year 2025. If you haven’t heard of IoT (Internet of Things) before, it refers to any ‘thing’ that is outfitted with sensors or technology which allows them to exchange data with other devices that are also connected to the Internet. Waverley is a company with a deep understanding and expertise in IoT applications working on the latest technology in IoT – if there is a developing IoT trend, we’ll catch it.

Waverley Software has worked with clients in numerous industries such as home automation, robotics, and energy analytics – all projects based on IoT development services. Coming from our experience with IoT applications and observing our recent projects, we came up with this list of IoT trends to watch in 2024 and moving forward. This article will brief you with all you need to know about the state of the industry!

IoT Market Overview

IoT Market Trends

Statistics indicate that the IoT market is expected to develop at a CAGR of 26.1% over the coming years.

The IoT market revenue growth, in general, has a growth rate of over 21.3% for this current year. The change by segment is 21.4% meaning that currently, the IoT market volume has raised up to $1,387 bs.

The segments that are adopting IoT are Smart Finance, Smart Cities; Industrial, Healthcare, Consumer and Automotive IoT, among others. Out of these, the three sectors that have shown major growth are the Automotive, Industrial, and Smart Finance sectors, having a larger growth rate from 2022 up to 2024.

The following list is a short comparison of the market size by sector in 2022 and currently in 2024:

 20222024
Automotive IoT300.30494.20
Consumer IoT173.90192.40
Healthcare IoT79.03108.60
Industrial IoT226.20325.80
Smart Cities74.24104.80
Smart Finance46.52113.30
Other IoT97.24132.00

We now connect with our surroundings in a completely new way thanks to the IoT. It has penetrated our homes, offices, places we often visit as customers or patients. But what does this quickly developing technology’s future hold? Exciting trends and future developments are anticipated for the IoT, including the spread of 5G connectivity, the rise of edge computing, and much more.

Moving into 2024, we can expect a surge in IoT device usage. The overarching theme of IoT trends in the coming year will be the increasing ubiquity of smart devices that consumers and the average person will have the chance to interact with in their daily lives. Expect to see IoT market trends point towards devices becoming more affordable and introduced to household goods and found in common interactions in society.

  • 5G Connectivity
  • Machine Learning & AI
  • Digital Twin
  • Edge Computing
  • Manufacturing & Agriculture
  • Transportation & Supply Chain
  • Energy, Buildings, Smart City
  • Healthcare and Wearables
  • Security & Data Regulations
  • Smart Home & Customer Assistance
  • Blockchain

In this article you will see a thorough description of each of the recently mentioned trends and future developments.

Impact of COVID on IoT

The COVID-19 virus and the regulations passed to limit the spread of the virus have far-reaching effects on the state of Internet of Things trends, technology and devices. As there is a push to minimize contact and create physical distance between people due to COVID-19, IoT offers tools to accomplish this.

Enhanced safety precautions introduced from COVID-19 and the pandemic will create an increase in touch-less technologies that you may interact with on a daily basis. We will see more options for payment while checking out at stores. While traveling, the introduction of check-in services that do not require an agent will become more widespread. You may check-in and board your plane at the airport without an agent assisting you.

To increase public safety, COVID-19 IoT devices might help to manage the occupancy levels of venues or restaurants. Scanners at entrances and exits will be able to keep a running tally of how many people are inside at once in real time, so as to not overload the venue.

In terms of sanitation, sensors placed outside of restrooms, will be able to tell at what frequency and how many people have used the restroom in a given period of time. This will allow sanitation workers to clean according to use and not just according to time that has passed. IoT devices will be put in charge of monitoring air quality of spaces and perhaps increasing filtration when it is needed.

The future of IoT technology may play a bigger role in security since people are working from home, more security will be needed for devices that have access to company data. Phones and computers that are logged on to company servers will be the primary target of hackers, ransomware threats, and viruses. Companies will be forced to ensure that employees’ devices are secure and use IoT technology trends to make sure that no devices are compromised.

5G Connectivity

Being the next generation in cellular network technology, 5G will continue to be rolled out throughout the coming year. Surpassing the previous 4G ins every regard, 5G will bring more bandwidth and much improved download speeds to all devices. 5G is one of the top IoT technologies that will become widespread. The new power of 5G will allow for wireless data transfer speeds that we haven’t seen widely available yet. These high speeds will enable low device latency, alway-on connectivity, and larger coverage to impoverished parts of the world that may be lacking physical wireless connectivity infrastructure. We may begin seeing 5G implemented in IoT devices such as self-driving cars, real-time robotics, disaster recovery equipment – all IoT devices that need uninterrupted connection and heavy data usage.

Machine Learning and Artificial Intelligence

Machine Learning and Artificial Intelligence - IoT Trends

As more and more devices go online and users are on their devices at unprecedented levels, it is no longer feasible for humans to sort through data because the rate at which it is created is uncontrollable. Instead, we must resort to machine learning and artificial intelligence to help us manage the data and make use of it all.

Machine learning is using an algorithm that improves itself as it gains more data. This Internet of Things technology pairs perfectly with Big Data, which is a massive volume of data that old methods of data analysis can’t process efficiently. As Machine learning accumulates large amounts of data, it can make more accurate predictions. Intelligence IoT can provide companies with a competitive advantage allowing them to increase analytical and predictive abilities, boost risk management, scale faster, and identify money and time-wasting pitfalls within the company.

Artificial intelligence IoT examples might include robots that track inventory at warehouses, smart home appliances that learn users’ behaviors or preferences and adjust accordingly, and also self-driving cars that can correctly predict traffic situations.

Machine learning and Artificial intelligence IoT solutions will be implemented into self-driving cars that can predict traffic movements from vehicles and pedestrians or smart home devices like thermostats that adjust naturally to user’s preference or to the local weather conditions, we might see automated robots that scan and monitor stock in a warehouse or store.

Collaboration Between IoT and Edge AI Technologies

The fusion of IoT and edge AI technologies has the potential to revolutionize various industries and drive innovation in the digital age. It empowers real-time data processing, analysis, and decision-making at the network’s edge, leading to improved efficiency within IoT systems and a decrease of latency.

The collaboration of IoT and edge AI can be found in many different industries. Yet, we will focus on IoT devices utilizing edge AI for tasks such as image recognition and voice processing:

  • Smart Security Cameras
    These types of cameras, which are equipped with edge AI, have the ability to analyze video footage in real-time. It is no secret that they can perform facial recognition as well as they can detect objects and track motion.
  • Smart Home Assistants
    Among the IoT devices that use edge AI are Amazon Echo, Google Home, and Alexa. They don’t have to completely rely on cloud-based computing in order to do speech recognition tasks, particularly those involving natural language processing.
  • Wearable Devices
    There are other monitoring devices such as fitness and health trackers, smart watches and more. When looking to analyze biometric data, such as heart rate, sleep and other activities in real-time, these wearable devices have become a real gamechanger, accompanying us throughout our daily lives, catching inconsistencies in a heart rhythm and notifying a physician if needed.

Digital Twin

A digital twin is another developing IoT trend and what it does is exactly as you might expect. It is a virtual asset that corresponds directly with a physical object. This allows for the object to be thoroughly tested digitally before it is implemented into the real world. Using real-world data, a Digital twin can provide accurate simulations of how the program would function in the real world without risking security or resources by demoing it on a live service. A digital twin is an emerging Internet of Things technology that is useful for saving money as well as for testing. Digital twin technology may benefit the manufacturing, automotive, and healthcare industries by allowing them to check production processes, model traffic conditions, and work to predict patients’ health based on comparing vitals digitally – all in real-time.

Edge Computing

Edge computing allows for us to get shorter response time and save bandwidth. Edge computing considerably reduces the amount of data to be transmitted, the traffic, and the distance this data has to travel. Edge computing will shorten the trip for data by placing the user closer toward the data or server that they actually need to be using.

In the age of Big Data, which is huge amounts of information that grows exponentially, there is seemingly limitless data being created, the physical infrastructure can only handle so much at a time. Edge computing will allow for less frequent slow-downs in speed when many users are using the network at the same time. This type of IoT technology will help with processes deliveries and self-driving vehicles.

The emergence of edge computing in the IoT has changed how data is processed and evaluated. Edge computing moves data processing and analytics closer to the edge devices themselves rather than being developed on centralized cloud servers.

Edge computing is important because it improves offline operation in disconnected contexts, increases data privacy and security by processing sensitive information locally, providing scalability and flexibility in IoT deployments. This being said, by bringing computing power closer to the data source, edge computing speeds up the transfer of data processing.

By decentralizing computational power and data storage, edge computing makes it possible to process data in real-time and decreases latency. It moves processing power closer to the point of data generation rather than depending on centralized cloud infrastructure.

Now, there are a lot of benefits of edge computing, but let’s look at them in terms of:

  • Enhanced Security: By processing data locally at the edge of devices or edge servers, edge computing reduces the exposure of sensitive information to potential security threats.
  • Improved Efficiency: Efficiency is increased by offloading computational workloads from the core cloud infrastructure through edge computing. Greater resource efficiency, faster reaction times, and less network congestion are all made possible by local processing and analysis at the edge devices.
  • Reduced Bandwidth Usage: Edge computing allows for a decrease in utilization by filtering, collecting, or compressing data locally before sending it to the cloud. In this manner, the amount of data that needs to be carried over the network is kept to a minimum, resulting in lower bandwidth costs and better performance.

IoT Data Analytics and Visualization

For IoT-generated data to reach its full potential, data analytics and visualization are crucial. The IoT’s rapid expansion has greatly increased the enormous amount of data that IoT devices generate in a variety of industries, including healthcare, energy, transportation, smart cities, and others.

With the use of data analytics, you may manage and assess vast amounts of data in order to get in-depth knowledge and make quick judgments. You can also utilize more sophisticated analytics approaches, such as machine learning and predictive modeling, to find patterns, identify anomalies, and derive relevant business information from IoT data.

There are several advanced tools for data analytics and visualization. These are crucial because they give businesses the ability to evaluate and make sense of the enormous volume of data that IoT devices generate. These IoT technology trends are useful for a variety of purposes, including converting unprocessed Internet of Things data into a format that is better suited for analysis. They also offer a means of visually and intuitively representing the data that has been evaluated. Advanced analytics tools also make it possible to apply a variety of analytical methods to IoT data in order to extract insightful information.

IoT data analysis is crucial for improving decision-making, optimizing processes, and enabling predictive maintenance, in short. These enable the real-time collection of data from connected devices and the use of that data to guide decisions and actions by utilizing the capabilities of IoT sensors. Each of these domains has benefited from IoT data analytics in the following ways:

  • Enhanced Decision-Making
    You may gain a greater knowledge of how sensors work via data analytics. By analyzing enormous amounts of sensor data, it can assist you in identifying trends, identifying abnormalities, and making data-driven decisions.
  • Processes Optimization
    You can detect inefficiencies, streamline operations, and decrease downtime with IoT data analytics to optimize processes. Monitoring and analyzing IoT data in real-time enables early detection of probable faults or potential risks.
  • Predictive Maintenance
    IoT methods are used to predict when equipment breakdowns are likely to occur based on real-time sensor data, predictive maintenance uses IoT data analytics as a key enabler.

Conclusion

As IoT technologies advance, we will see more widespread adoption of IoT systems and an influx of applications – much more than described in this article. There are currently 34,000 that are making use of IoT technology, which is a 27% increase from the previous year. Future IoT developments seem limitless, as new brilliant ideas are launched and ingenious IoT products are created, we will see the world becoming a more efficient and comfortable place to be.

FAQ

What is IoT, and why is it important?

The “Internet of Things” (IoT) is a network of physically connected gadgets, vehicles, and other items that have sensors, software, and network connectivity for data collection and sharing. It is, to put it briefly, the concept of connecting everyday objects to the internet and enabling them to communicate with one another and us.

Which is the future application of IoT?

Future IoT applications are very versatile.. In Healthcare that’s smart medical equipment, tailored treatment, and remote patient monitoring. IoT will be used by smart cities to streamline resource management, enhance urban planning, and other tasks. Automation, predictive maintenance, and supply chain optimization enabled by industrial IoT will alter production processes. IoT will also improve wearable technology, home automation, and smart energy management, enabling more pleasant and energy-efficient living.

What are the key technologies driving the Internet of Things (IoT)?

The technologies vary from wireless connectivity tools such as wifi, bluetooth and LTE to back-end technologies such as C++, front-end (for IoT Apps) such as React, etc. Then there is sensor technology, which helps to detect and measure different parameters like temperature, motion, light, etc. Machine Learning tools such as Tensorflow or PyTorch can be used to process the data gathered by IoT devices.

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WT
Waverley Team
Content Writer
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