How powerful AIoT will change the way we live

10 Nov

In the past decade, we have seen two major advancements in technology. The first is AI, which has gone from identifying objects in pictures to generating text that can pass medical exams. The second is the IoT, which has taken our everyday objects and made them controllable from half the world away. One of the next evolutions of technologies is expected to be the Artificial Intelligence of Things (AIoT).

The AIoT is a fusion of the two fields of AI and the IoT and is set to revolutionise the way we live. It will impact industries from healthcare to agriculture. As the AIoT develops though significant challenges and concerns such as data privacy, security and ethical concerns arise.

What is the IoT

As the IoT and AI continue to evolve, we expect one of the major emerging technologies to be AIoT. To explain its potential, let us take a deep dive into the impact of the IoT on our lives.

The IoT refers to devices that may use sensors, processors, and software to communicate with other devices or systems that are connected in a network. This network doesn’t necessarily need to be the internet; communication can occur via Bluetooth, Wi-Fi, or cellular data.

Generally, IoT devices are equipped with a variety of sensors that can detect environmental conditions, such as temperature, humidity or moisture. This sensor data is then processed by the IoT device into a useful form before communicating with a connected server.

The user can then remotely monitor and control their devices from this server via a webapp or mobile device.

The IoT has impacted a wide range of industries allowing for consumers to better control their thermostats to industrial clients better understanding the condition of their machinery.

In fact, we here at Beetlebox, speclise in setting up automated flows specifically for developing and managing IoT devices.

What do we mean by AI?

Artificial Intelligence is a very broad term that roughly means the ability for machines to mimic problem-solving skills to solve tasks. When referring to the IoT, we are generally referring to a specific section of AI algorithms known as machine learning or deep learning.

Machine learning algorithms use statistical methods to train on a dataset of input and output data. Often machine learning algorithms require human intervention for learning. After training the algorithm is then able to make predictions based on new input data.

Deep learning is like machine learning, but generally consumes large amounts of unstructured data in its raw form, such as text or images, and needs less guidance than classic machine learning. This makes it easy to build large datasets and for the algorithm to derive key insights into that data.

Popular techniques in deep learning include Neural Networks. These are made of layers of artificial neurons that can be trained to make predictions based on input data. They are often used in AIoT applications because once they have been trained, they can be optimised to become computationally efficient.

Fusing IoT and AI into the AIoT

The AIoT is simply the fusion of AI technology with the IoT. More specifically, it is the use of AI to analyse the data produced by the IoT devices. One of the most important aspects of the AIoT is exactly where this data is processed:

Cloud computing: In this scenario, the IoT devices are kept the same as they were, but the data extracted from the devices is stored on the Cloud to form a data lake. This data lake can then be used to train AI on the Cloud to make predictions for users. For instance, if we were using the IoT for monitoring the temperature of an industrial machine over time, we could send that data to the Cloud and use AI to predict what the exact temperature would be at a future date. This prediction can then be sent to the user via a web application.
Edge computing: The advancement of cheap processors has allowed us to move away from Cloud computing to running on the device itself. In this scenario, the device processes the data it produces through AI algorithms and only sends the relevant data through to any servers. An example of this would be autonomous vehicles where all the sensor data is processed on the vehicle itself and the Cloud is not relied on.
Hybrid computing: There is also the potential to run both AI on the Cloud and the Edge. In this hybrid model, the IoT devices can be used to run relatively simple algorithms that can filter data or make modest decisions. Data can then be sent through to the Cloud to run deeper AI that is trained on a larger amount of data to make decisions. The most popular example of this algorithm are smart speakers, such as Amazon Echo. Most of the time they are not sending any data to the Cloud, but when a user says a ‘wake word’ the device will then send data through to the Cloud for the user’s speech to be processed.

Thanks to the versatility of the different AI models, they can be applied across a wide range of industries from healthcare to agriculture. Let’s look at some of these now.

Using AIoT for better preventative healthcare.

Monitoring our own personal daily health requires a wide range of devices from weight scales to blood pressure monitors. These devices though they often only provide a single data point in time to which we need to make important healthcare decisions, such as changing our diets.

It is often proposed that we could connect these devices into a single network that could then communicate and store the data in the Cloud. We can then encourage the user to take regular measurements with their devices and we can start presenting a range of different data points over time.

How about interpreting this data? Doctors are busy enough without patients coming in with reams of data asking what they should do about their seemingly random fluctuations. This is the importance of AI. Through AI, we can gain an understanding of whether a person is healthy and provide simple recommendations to lifestyle changes that would benefit them over long periods of time.

This could promote preventive health care and improve the patients’ well-being with the ultimate goal of preventing disease, disability and death.

Improved agricultural management.

Despite centuries of advancements, agriculture remains heavily dependent on human labor, especially during the harvesting of crops. This work is often difficult and can have long-term health consequences for the labourers.

The reason we still use manual labour is because the operations are often ill-defined or undefined and that the nature of crops is messy. Think about how difficult it would be for a robot to identify all the different forms of fruits, stems, and leaves that are possible in a single type of plant. Now add to that the variations in light, landscape and weather.

Fortunately, the AIoT may be able to address many of these difficulties. AIoT empowered UAVs may be able to identify and pick ripe fruit as well as detect problems, such as disease, stress, or pests.

Smart sensors may also closely monitor the conditions of the soil and crops, to best enable crop management.

Save money and hours of chores with smart homes and AIoT.

Often when we think about our consumer technology, we think about it as a variety of separate gadgets that do not interact with one another Our thermostat is different from our smart doorbell, which is different from our washing machine.

However, these systems are all interlinked with each other and the AIoT allows us to change the way we interact with our homes.

A smart home will be able to detect the optimal heating times based on the occupants’ presence in the house. It also reduces the build-up of humidity and dampness in the house, preventing the growth of mold. Washing machines can be turned on when energy demands are lowest, providing a cheaper wash to occupants.

Numerous subtle improvements for our everyday devices can be made with better data analytics. By combining all this sensor data together, we can make homes more energy efficient, secure and save on hours of chores.

Efficient and autonomous logistics.

The IoT has already made a significant impact on the logistics industry. Wireless devices are used for tracking shipments and monitoring container temperature and condition. This technology can also be used in inventory management to track location and inventory levels.

With the introduction of AI, companies can enhance their smart warehousing solutions. Autonomous mobile robots can navigate warehouses and handle inventory. Effective tracking allows the robots to know the exact location of all inventory at any time, reducing the need for manual labor and increasing accuracy.

Smart cities that provide a high quality of life for their residents.

When thinking about smart cities, we often imagine ourselves zooming around in autonomous vehicles with smoothly flowing traffic. This is one of the benefits of a smart city, where vehicles can communicate with each other and the traffic management system. This would enable better traffic light control, as well as dynamic rerouting based on not just current traffic but also expected traffic build-up.

Smart cities, though, can also benefit public transportation with autonomous trains, trams, and buses, meaning that slowdowns due to available drivers are no longer a factor. We can even divert that human labor to create conductor jobs, ensuring that journeys are safe and comfortable.

It can even help improve public health through better services, such as waste management and pollution control. We can have sensors placed in public bins that show when they are overflowing, reducing the spread of vermin. We could produce pollution maps for residents, so people can avoid high pollution areas if they wish.

Challenges and concerns

Whilst we have painted a utopian picture of the AIoT so far, the creation and processing of the data we produce every day also have the potential for misuse. There are major privacy, security, and ethical concerns when it comes to using the AIoT.

In healthcare, we can gather this data for better preventative healthcare, but it can also be misused by insurance companies to prevent people from getting insurance because they have detected that a person has a pre-existing condition before the person is even diagnosed.

Smart agriculture may lead to an increase in the use of pesticides, herbicides, and fertilizer if applying such chemicals across multiple fields becomes as easy for the farmer as pressing a button. These chemicals can have detrimental effects on both consumers and the local environment.

When it comes to privacy and security, smart homes also face a major problem. Whilst it can be great to use smart doorbells to detect if a home is occupied, this information is also valuable for criminals. It is also useful for oppressive regimes that are looking to track the location of certain citizens.

Smart cities and logistics may also be great for businesses and residents, but autonomous vehicles used in public transport and warehouses may potentially lead to mass redundancy for all the previously needed workers. This could lead to an increase in poverty rates in that city and end up hurting the very citizens smart cities were supposed to help.

Conclusion

We have already seen the impact of the IoT, but the merging of the IoT with AI will usher in a new wave of innovations. The AIoT will have a transformative effect across multiple industries, including healthcare, agriculture, consumer electronics, logistics, and public infrastructure.

Taken as a whole, these effects have the serious potential to change the way we live, making everyday tasks at home or at work more efficient. It can even have a positive impact on the quality of life by improving preventative healthcare and reducing our exposure to pollution.

At the same time, the AIoT presents a real risk of misuse. Processed data in the wrong hands can be used to control and manipulate people, as well as cause financial devastation.

If managed properly, though, the AIoT can have real positive impacts for all of us. Our everyday data presents new opportunities for us to live better lives, and we have only seen a fraction of what is to come.

If you are a developer working in the IoT, AI or AIoT industry, you may be wondering about how to build the infrastructure to manage your devices. At Beetlebox, we provide solutions for automating your workflows and are offering free demos, which you can immediately book here.