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2022 Nov
28

AI and IoT combining to improve decision making in 2022
Last Updated 27 minutes ago
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It has been years since the number of Internet of Things (IoT) devices in all
fields has exploded. Automating medical devices, homes, and buildings to
industrial processes! All these devices are connected, including portable
devices, sensors, and medical monitors, allowing huge amounts of data to be
collected (Big Data).

By 2025, IDC estimates that there will be 55 billion connected IoT devices
creating about 80 zettabytes (ZB) of data.

There is a strong correlation between wireless connectivity and this growth.
This technology enables things to communicate and connect to one another over
the Internet. Hyper-connectivity provides many advantages, including automated
control, easy communication between devices, and large data exchange.

The introduction of artificial intelligence (AI) will enhance the utility of IoT
even further. By embedding intelligence in connected devices, they can collect
and share data, analyze it, learn from it, take decisions, and act on them
without human intervention.

AIoT ( Artificial Intelligence of Things ) is a combination of AI and IoT that
automatically makes decisions based on the data they generate.

As a result of new AI technology, intelligence can be deployed at the edge and
cloud analytics can be significantly reduced in cost and time. AIoT brings
computing closer to data in this way. Additionally, AI technologies, running on
edge devices, can analyze and make decisions based on data generated by sensors
and IoT devices, such as temperature, pressure, humidity, vibration, and sound.

A large part of AI applications ran on the cloud in the beginning due to the
complexity of machine learning models. Some applications, however, cannot be run
in the cloud due to lack of connectivity or bandwidth. Other applications
require that the models run on the device itself.

In such cases, the cloud couldn't be used since its latency prevents real-time
operation. This type of application can also be found in virtual assistants,
industrial control, facial recognition, and medical devices requiring immediate
responses in real time.

The local device also may be required to store and process data due to security
and privacy concerns.

Hence, Edge AI offers undeniable benefits. Some of those benefits include
autonomy, lower latency, lower power, lower bandwidth requirements, lower costs,
and greater security. This makes it more attractive for emerging applications.

The use of AI is becoming increasingly common in IoT applications, including
vibration analysis, speech processing, image classification, and computer
vision, which require a combination of computational power from DSPs and
inferences from machine learning.

Enhanced operational efficiency Through AIoT, business results can be optimized
by processing real-time operational data and identifying patterns, which can
lead to higher operational efficiency. The production process can be improved
and the workflow can be improved, increasing efficiency and reducing operating
costs.

Better risk management: By identifying risks and utilizing these insights,
traders can increase security, reduce losses, and make better trading decisions.
A good example would be predicting mechanical problems in airlines or detecting
security risks in production facilities.

Voice recognition, facial recognition, and predictive analytics are among the
new products and services brought about by AI. Many applications are possible
with these capabilities, such as using robots in delivery services, search and
rescue operations during disasters, and predictive maintenance for cars or
buildings.

Business disruption caused by unplanned downtime in manufacturing can be very
costly. By https://www.webdesigningcompanies.com/ , AIoT helps anticipate
failures and reduce downtime costs and incidence.

AIoT helps to personalize the shopping experience in the retail environment by
providing tailored recommendations based on customer demographics.

Edge AI helps reduce the volume of data that must be transferred to the cloud,
thereby reducing the cost of cloud connectivity.

The technology is used for creating intelligent agricultural systems that adjust
parameters based on weather conditions, water consumption, temperature, and
crop/soil conditions.

Artificial intelligence is used by robots to sense complex environments and
adapt their responses, whether in manufacturing, package/food delivery, or
search and rescue operations in disaster zones.

AI-enabled machine vision improves quality control on the assembly line and
helps detect anomalies. As a result, machinery can be maintained more
effectively.

An autonomous vehicle can keep a close eye on traffic, weather, and road
conditions, or it can predict pedestrian behavior and act accordingly.

Building/Home Automation: Facilitate energy efficient building operations by
adjusting lighting and climate control based on usage and preferences. Moreover,
it enables automated access control and improves predictive maintenance.

Waste management, parking management, traffic management, and smart lighting are
some of the services that are part of the concept of smart cities.

wordpress website designers and transportation : Improve fleet management with
proactive maintenance using predictive maintenance technology.

Analysis of data for better business decisions and recommendations that improve
the user experience in retail management.

Medical: Applications include detecting and diagnosing diseases using image
data, controlling patient information remotely, and sending alerts when
abnormalities are detected.
https://b3.zcubes.com/v.aspx?mid=9663070&title=ai-and-iot-combining-to-improve-decision-making-in-2022

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