Artificial intelligence, machine learning, and the Internet of Things are being used to improve environmental monitoring in several ways. Sensors are deployed to monitor air and water quality, temperature, pollution levels, and other environmental factors. This data is then analyzed using AI and machine learning to identify patterns and critical issues. These technologies also help monitor crop and soil conditions, as well as endangered species, in order to promote more sustainable agricultural practices and protect biodiversity. Going forward, the use of AI, ML, and IoT in environmental monitoring is expected to increase further.

1. Session 1
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Artificial Intelligence has long been in existence, and it finds myriads of uses
across the different business sectors. Coming to some of its unconventional
methods, then AI finds application in environmental monitoring. Yes, we all know
that AI, ML or IoT have increased their presence in our life in different ways, but
only a few of us understand how dramatically these technologies have brought in
the paradigm change. In recent years, we have seen companies realizing the
growing importance of artificial intelligence training and machine learning
training. The aim of these technologies is to enhance the functioning of the system
and make them work more like a human. Well, it requires the expertise of
expertise, and so we have a higher demand for artificial intelligence experts and
ML experts. But, in this blog, we are going to highlight how IoT, ML and AI are
making an impact on environmental monitoring.

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IoT can prove helpful in monitoring the environment by managing the energy and
other resources that are being contaminated every day. If we go by the
conventional methods of monitoring the methods, samples are collected, then
analyzed analytically. There are two ways to collect and track this data. One if the
manual process which is time taking and there is a higher probability of error. The
second method is instrumental, wherein tools and software are used to assess the
collected data and then come up with a result. If we compare the two methods, we
can claim that instrumental methods are faster and also less prone to error.
When we talk about the IoT monitoring environment, then we are talking about
waste management, weather conditions, resources, pollution level etc.
Let's explore the importance of AI, ML
and IoT in environmental monitoring:
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A lot has been done in this domain. One such example is that of an air quality
system that records the particulate matter or PM. This system categorizes PM
into PM10, PM 2.5, and PM 1. When the particulate matter goes into the lungs, it
can cause some severe health issues, hence keeping a check on the same plays
an integral role. Standards are being implemented to monitor this and check on
the factors that can impact the same.The next question that pops up is why do we
need IoT for this and how it is going to create a difference. If we dig deeper into
environmental monitoring, then it is way more profound than what we know. It
requires the study of complex data that will highlight the critical factors impacting
the environment and is there any set pattern of increased or decreased impact.
While this can be studied using conventional methods, what we need is a deeper
understanding of the same. To make the process flawless and faster, we need
advanced systems like AI, ML and iot training.
Why do we need IoT?
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1. Proximity sensors
2. Temperature sensors
3. Water quality sensors that keep a check on BOD, COD, pH and other microbial
contaminants.
4. Gas sensors which assess the quality of air
5. Smoke sensors which are used for checking the industrial and environmental
conditions in the more prone areas
Sensors are being used to assess the
environment; these are :
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Pollution is one of the reasons that impact the productivity of the soil. Intensive
use of pesticides does impact the environment. Thousands of people die every
year because of the chemicals, and pesticides that are being used while farming.
Implementation of AI and IoT for environmental sustainability includes methods
like monitoring the crops, soil and crop production with low impact on the
environment. With the help of these technologies we can aim to have safe
agricultural methods which are going to increase productivity. For those smart
monitoring devices and sensors can be attached to the crops to monitor their
growth continuously. With the help of these sensors, we can assess the hydration
needs of the plant, nutritional needs and based on it, healthier and safer
agricultural methods can be adopted.
How IoT and AI can prove helpful?
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Another aspect of using AI and IoT is by protecting the species. We have vast
biodiversity. And there are various species which are on the verge of extinction.
With the help of the IoT and AI tools, we can study the different patterns in animals
like feeding habits, migration and mating. It helps in keeping a track on animals
without disrupting their normal life. A US-based company is using computer vision
to detect the footprints of cheetahs, rhinos and other endangered species to know
what is impacting their life or putting them in danger.
These are the few of the examples of the companies that are using AI, IoT and Ml
in the field of environmental monitoring.
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Conclusion
In the times to come, we are going to see greater use of these technologies.
Hence, a rise in the demand for professionals in this field is going to rise. Opting
for IoT training or artificial intelligent training or Machine Learning training is
going to pave the way for a brighter future.
Global Tech Council is here to bring the changes and help you escalate the growth
in your career by offering the right learning platform for AI, ML and IoT. To explore
more connect with Global Tech Council today.

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