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Environmental Monitoring System using IoT, AI and ML

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AI, ML, IoT, and Emerging Tech. Cognitive technologies like machine learning and AI (artificial intelligence) certainly have proven to be an important part of the IoT (Internet of Things) sector because they can help make products and services smarter and, therefore, more valuable. – PowerPoint PPT presentation

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Title: Environmental Monitoring System using IoT, AI and ML


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  • 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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Let's explore the importance of AI, ML and IoT in
environmental monitoring
  • 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.

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Why do we need IoT?
  • 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.

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Sensors are being used to assess the environment
these are
  • 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

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How IoT and AI can prove helpful?
  • 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.

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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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