Industry experts compare the launch of AI to the invention of the printing press or the first personal computer. It has become one of the leading software development areas with vast growth potential. Over 50% of businesses have already adopted AI to their operations, and 76% of enterprises report increasing investments in AI in 2023. Statista’s data suggests that the...
The power of technology is huge in the 21st century. We use 5G Internet, smartphones, chatbots, and smart homes daily. What do you think, have we gotten far enough in the last 20+ years? And the wheel continues spinning.
When two groundbreaking innovations merge into one, the world shutters just a bit. An inevitable change happens, and we begin dealing with certain things differently.
Today, we will find out how the duet of AI (Artificial Intelligence) and IoT (Internet of things) impacts people’s lives and businesses. What has changed, and in what way? Our article covers the latest innovations and particular benefits brought by the combo of smart devices and intelligent analytics.
A Match Made in Heaven? Why AI and IoT Work Well Together
Let us start from the very basics to make things as clear as possible. What is IoT in simple terms? This is a system of devices connected via the Internet, acting based on some gathered data. But this data does not work on its own. It should be collected, stored, and processed before being used for decision-making. That is where everything starts falling apart.
IoT is surely (and quickly) spreading around the world, and organizations are facing the dilemma of quality data analytics. Meanwhile, the amount of data is growing every second, and the issue becomes more visible. Let us figure out why this issue is happening.
First, there is a cloud problem. Incoming data volumes are so big that clouds cannot scale proportionally. Second, there is a transportation problem. The capabilities of transferring all the data from an IoT device to the cloud are limited. Even if an organization’s infrastructure is well-developed, growing data volumes put sticks in the wheels.
Now let us turn to the recent IoT innovations. Autonomous cars, for example, require real-time decision-making (similar to human driving) by all means. Otherwise, the technology will not bring the desired results.
The same goes for IoT applications in manufacturing. Imagine unexpected delays right in the middle of the production process. How many consequences, in your opinion, may it have?
These numbers will give you an idea of what is going on in the AIoT (AI + IoT) niche at the moment.
IoT Adoption Tendencies, Operational Challenges, and AIoT Market in Numbers
As we mentioned, IoT implementation is becoming a trend. According to the survey conducted among 260 organizations by the Eclipse Foundation, only 4% of respondents have no plans for IoT deployment. At the same time, 53.5% have already deployed IoT solutions, and 20.2% are planning to do so within one year.
But any innovation involves a number of new challenges that (unsurprisingly) require innovative approaches. Thus, processing and managing IoT data is a top challenge according to the Eclipse survey (22.8% of respondents). Plus, 12.1% find it problematic to extract useful data from sensors.
IoT implementation trends and challenges naturally lead to changes in the AIoT niche. The Mordor Intelligence research states that the AI in IoT market is expected to grow with a 7.86% CAGR from 66.12 billion USD in 2022 to 106.91 billion USD in 2028.
North America is the largest AIoT market, and the fastest AI in IoT adoption growth will be witnessed in the Asia-Pacific region. The growth rate will be low only in South America, which proves the niche will evolve pretty much evenly across the globe.
As you can see, artificial intelligence is vitally important for innovative IoT projects. Some experts state it may cause massive transformations in many industries. The next section will give you an idea in what way transformations may occur.
AI Algorithms for IoT: What Are the Best-Case Scenarios?
AI is not that simple. It includes several subsections, such as machine learning, deep learning, computer vision, speech recognition, and others, used separately or in combination with one another. And each of them can be implemented to achieve spotless performance of an IoT system.
Retail: Advanced Analytics and Checkout-Free Shopping
Not so long ago, we associated all retail innovations with e-commerce platforms. But time flies, and innovations enter the doors of offline stores, providing previously unachievable customer insights and experience. It becomes possible thanks to affordable IoT sensors and computer vision solutions.
Now retailers can track customer traffic within a store using smart cameras that provide information on the shopper’s behavior and choosing process, as well as allow business owners to optimize the store’s space according to shopping patterns of their target audience.
Moreover, autonomous offline stores have already entered the retail industry. Take the example of Amazon Go opened in the US and the UK. Shoppers in such stores use only a special app to enter and nothing more. This checkout-free experience was named “Just Walk Out”.
IoT sensors and cameras placed all over the store capture the products that customers grab from the shelves and add it to a sales receipt in the Amazon app. The total sum is withdrawn from the customer’s payment card synchronized with the app.
A similar experience is now offered by a Lisbon startup Sensei. Just like Amazon Go, Sensei uses a blend of cameras, sensors, and AI algorithms to provide “grab and go” shopping. Apart from obvious advantages, it appears to be particularly beneficial in the pandemic era because it eliminates any queuing.
Healthcare: Body Trackers
The mix of IoT and AI used for healthcare purposes is now called the Internet of Bodies (IoB). It refers to a network of devices that collect, process, and transfer data about the human body to interested parties, be it users themselves, doctors, or researchers.
The examples of IoB devices include well-known fitness trackers, implanted devices, or ingestible sensors that can monitor pretty much any aspect of human health. The IoB data is objective and collected throughout the day, which makes it the most trustworthy source of information about the user’s health condition.
Similar solutions are also implemented in sports or other industries associated with physical efforts. By measuring the state of the worker’s or athlete’s body, managers (or coaches) can adapt workload to each person individually.
Ford has employed the body tracking technology used in sports to keep a closer eye on the workers’ safety and reduce the injury rate during the production process. It is a part of a bigger program initiated in 2003 which eventually has led to 70% decrease of injuries happening at the assembly line.
Smart homes are a well-established niche in the IoT industry that is evolving and becoming more sophisticated every year, growing at a projected CAGR of 12.47%. Smart devices placed across a household can control lighting, heating, virtual assistants, security tools, kitchen appliances, and many other things.
In combination with AI algorithms, smart devices can “make a decision” to perform a certain action with no human involvement. Raw data collected by the IoT systems is transformed into behavioral patterns that simplify people’s daily routines. Here is a market example to demonstrate this AIoT workflow.
Google has launched the Nest learning thermostat that collects data of how people use the device over time and creates scenarios to set up comfortable temperature in any circumstances. It also helps save energy by adjusting temperature when users are not at home.
Agriculture: Monitoring Systems and Automated Machines
Agriculture is one of the industries where the trace of AIoT is the most considerable. Smart agriculture systems impact various aspects of farming activities, such as monitoring crops, controlling utilization of water, electricity, and fertilizers, analyzing and predicting the harvest, etc.
All these tasks are accomplished by the following types of IoT technology solutions:
- Precision farming systems covering various activities (monitoring soil moisture, managing water consumption, optimizing irrigation, and more) with the use of sensors and autonomous machines;
- Ground- and air-based drones applied to monitor crop health, soil condition, and infestation, as well as spray crops or sow seeds;
- Smart greenhouses based on the work of sensors that together build up an environment to control crops’ growth and condition. Greenhouse sensors can autonomously regulate light, humidity, and temperature in response to collected information;
- Agricultural robots can partially replace routine manual tasks by harvesting crops and then sorting the yield. Robots are trained with AI to monitor crop condition and harvest it at the right moment;
- Solutions to monitor animals’ health and location that, for instance, can help farmers separate unhealthy animals and, thus, prevent a disease from spreading.
This list is not final, and it is regularly updated with new features and applications. But none of it would be possible or efficient enough without AI technologies, particularly, computer vision.
CHI Software’s team of IoT engineers created an automated solution for greenhouses for an urban farming startup aiming to make agriculture fun and easy. The main project goals included minimizing manual labor, improving efficiency of resource utilization, improving security, and building an Android application for remote monitoring.
As a result, CHI Software engineers automated the work of switchers and sockets, developed firmware and logic to control sockets and sensors, and, finally, built Android and tablet apps with an easy-to-use interface.
Transportation: Autonomous Cars
Autonomous cars can accomplish any driving action just like a human driver would do it. They do not require any human involvement and can get from point A to point B without drivers or passengers. The secret to the highest level of autonomy is in smart sensors, actuators, and, of course, algorithms that help make driving decisions in real time, instantly.
IoT-powered cars map up an environment around them using the mentioned sensors located in different parts of the vehicle. For example, radar sensors track the position of other vehicles. Similarly, light detection and ranging sensors help measure distances and identify road edges.
This niche is very promising for taxi, delivery, and other transportation services where IoT innovations can significantly reduce expenses and change the state of the labor market.
There is hardly anyone who has not heard about Tesla cars with self-driving features. However, it is not a complete autonomy, and the car still needs the driver’s presence. The innovation is still a work in progress, and we are sure that exciting news in this regard is coming soon.
Smart cities are probably the most complex IoT networks covering urban areas and collecting data on various events and conditions. One can say that the main goal of providing smart city solutions is to make people’s lives more pleasant and sustainable.
Some examples of smart city features:
- Smart parking to help drivers quickly find parking spots and conduct digital payments for parking services;
- Smart traffic management allowing governments to monitor traffic and optimize traffic lights;
- Smart road lighting that dims in late hours when roads are empty;
- Warning systems that can provide early signals in case of hurricane, earthquake, or flood coming;
- Real-time building monitoring that allows citizens to notify officials when repairs are required.
All these features can be implemented in combination with one another and form large and efficient IoT infrastructures. It is a real chance to make urban areas less stressful and reduce negative climate changes.
Some examples of already existing smart cities are Amsterdam in the Netherlands and Neom in Saudi Arabia. Singapore, Oslo, New York, London, and other cities have also been actively applying smart city instruments.
Real Benefits for Businesses: How AI and IoT Projects Can Help You Thrive
Some of the benefits become obvious after reviewing AIoT implementation scenarios. Let us sum up what we know about the niche by listing the reasons why companies should use AI tools for IoT to achieve their goals.
- Workflow optimization which takes place in any industry where AIoT is implemented. Technologies can automate routine tasks and reduce the impact of human error. They also help notice triggers immediately and act accordingly.
- Risk reduction. By noticing even minor changes as soon as they occur, technologies can literally save lives (and businesses). Be it a road accident or adverse weather conditions, AI helps smart devices quickly recognize the threat.
- Quality control. Computer vision solutions equipped with smart cameras can identify what product does not meet required standards and notify quality managers. It is especially beneficial if a business has to deal with a large production or small product details (for example, plant diseases in agriculture).
- Detailed 24/7 monitoring which enables to in-depth reporting and analytics. Objective results provided by tireless sensors can improve decision-making processes on all levels, starting from tactical steps up to strategic planning.
- Individual approach. Day-by-day data analytics creates usage patterns reflecting a particular person or business process. By noticing trends, AI plus IoT technologies adapt to any circumstances on the go, creating unique usage scenarios.
- Sustainability. Be it one smart home or a whole smart city, sensors in combination with algorithms help create eco-friendly environments that match human habits, traffic trends, weather forecast, and time of the day.
All of these advantages eventually lead to significant cost reduction. Moreover, they transform the cost structure, as some operations become redundant.
We live in the days when technology is not a luxury anymore. It penetrates all industries to a certain extent and forever changes our way of living. What is more important, technology helps us meet the challenges brought by the present day, such as global warming or pandemic.
We have learned today that AI and the Internet of Things take on one more tricky challenge – unimaginable amounts of data. Through the combination of machine learning, computer vision, and smart sensors, we can track our health, control soil conditions at farms, or monitor traffic in cities. And there is hardly a limit to new opportunities. How about giving a try to at least one of them?
IoT software development is an expertise area of the CHI Software team. We started building embedded systems ten years ago, in 2013, and have strengthened our expertise with AI engineering since then. If you are looking for a team to implement bold ideas in the AIoT industry, you are in the right place to start.
Polina is a curious writer who strongly believes in the power of quality content. She loves telling stories about trending innovations and making them understandable for the reader. Her favorite subjects include AI, AR, VR, IoT, design, and management.