The Internet of Things is a network of physical objects – vehicles, machines, home appliances, and more – that use sensors and APIs to connect and exchange data over the Internet.

IoT systems allow users to achieve deeper automation, analysis, and integration within a system. They improve the reach of these areas and their accuracy. IoT utilizes existing and emerging technology for sensing, networking, and robotics.

IoT exploits recent advances in software, falling hardware prices, and modern attitudes towards technology. Its new and advanced elements bring major changes in the delivery of products, goods, and services; and the social, economic, and political impact of those changes.

Internet of Things – Software

IoT software addresses its key areas of networking and action through platforms, embedded systems, partner systems, and middleware. These individual and master applications are responsible for data collection, device integration, real-time analytics, and application and process extension within the IoT network. They exploit integration with critical business systems (e.g., ordering systems, robotics, scheduling, and more) in the execution of related tasks.

Internet of Things – Technology and Protocols

IOT primarily exploits standard protocols and networking technologies. However, the major enabling technologies and protocols of IoT are RFID, NFC, low-energy Bluetooth, low-energy wireless, low-energy radio protocols, LTE-A, and WiFi-Direct. These technologies support the specific networking functionality needed in an IoT system in contrast to a standard uniform network of common systems.

IOT:- Key Features

  • IOT Meets AI:- All we need to do to create an accurate and working Machine Learning models is a huge amount of high quality and relevant data. Internet of Things (IoT) devices have the potential to generate a vast amount of data which can be then used with AI. Imagine facial recognition systems using cameras to replace ordinary payments, or recall the current hype for autonomous cars gathering data about surroundings using built-in sensors. Those solutions use both AI and IoT, yet little has been written on how to easily integrate them together. Fortunately, existing IoT platforms provides the interface to gather the data from various devices and can offer a relatively easy way to utilize the IoT data into AI/ML systems. This article will provide you with a few state-of-the-art AI+IoT examples, an overview of the most popular IoT platforms and how they can be integrated with your AI/ML systems.
  • Connectivity − New enabling technologies for networking, and specifically IoT networking, mean networks are no longer exclusively tied to major providers. Networks can exist on a much smaller and cheaper scale while still being practical. IoT creates these small networks between its system devices.
  • Small Devices − Devices, as predicted, have become smaller, cheaper, and more powerful over time. IoT exploits purpose-built small devices to deliver its precision, scalability, and versatility.

IoT – Environmental Monitoring

The applications of IoT in environmental monitoring are broad − environmental protection, extreme weather monitoring, water safety, endangered species protection, commercial farming, and more. In these applications, sensors detect and measure every type of environmental change.

  • Air and Water Pollution
  • Extreme Weather
  • Commercial Farming

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