IEEE 2024 – 2025 IoT Machine Learning Projects

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DHS Informatics: Leading Provider of IEEE IoT Machine Learning Projects for 2024-2025

DHS Informatics offers the latest IEEE IoT Machine Learning projects for final year engineering students for the academic years 2024-2025. Our comprehensive training program equips students with the skills needed to develop innovative IEEE IoT ML projects, ensuring they are well-prepared to submit high-quality projects and achieve excellent grades.

Expert Training in IoT Machine Learning

At DHS Informatics, we specialize in training students in IoT techniques, enabling them to create sophisticated Machine Learning with IoT projects. Our experienced instructors provide hands-on training and practical knowledge, helping students understand the intricacies of IoT and machine learning systems.

Placement Training Program: OJT – On Job Training

Located in Bangalore, DHS Informatics offers a unique placement training program called OJT – On Job Training. This program is designed for both job seekers and final year college students, offering them the opportunity to enhance their skills and secure job placements in top IT companies. Our training focuses on real-world applications of IoT and machine learning, preparing students for successful careers in the tech industry.

Extensive Experience in IEEE IoT Machine Learning Projects

With over two decades of experience, DHS Informatics has been a trusted provider of IEEE IoT Machine Learning projects for students pursuing B.E, B.TECH, M.TECH, MCA, BCA, and DIPLOMA degrees. Our projects are designed to meet the latest industry standards and academic requirements, ensuring that students gain relevant and up-to-date knowledge.

Machine Learning:

Machine learning is a type of artificial intelligence that enables computers to learn from data and improve their performance over time. It involves using algorithms to analyze data and make predictions or decisions without explicit programming. There are three main types of machine learning: supervised learning, where the computer is taught with labeled data; unsupervised learning, where the computer discovers patterns in unlabeled data; and reinforcement learning, where the computer learns through trial and error.

Machine learning is used in various applications, such as speech recognition, image recognition, and natural language processing. It can also be used to make predictions, classify data, and solve complex problems. The field of machine learning is constantly evolving, with new techniques and algorithms being developed to improve its capabilities.

IoT Machine Learning :

The fusion of the Internet of Things (IoT) and Machine Learning (ML) is a powerful combination that is transforming the way we interact with devices and data. IoT Machine Learning enables devices to collect and analyze vast amounts of data, making it possible to predict and automate various processes. This synergy has numerous applications across industries, from smart homes and cities to industrial automation and healthcare.

The future of IoT Machine Learning is promising, with potential applications in predictive maintenance, supply chain optimization, and enhanced customer experiences. IoT Machine Learning can help businesses streamline operations, reduce costs, and improve decision-making by analyzing real-time data from IoT devices. Additionally, IoT Machine Learning can be used to develop intelligent systems that can learn from user behavior and adapt to changing conditions.

In the future, IoT Machine Learning is expected to play a crucial role in shaping the way we live and work. It will enable the development of more sophisticated and efficient systems that can learn from data and adapt to new situations. As the technology continues to evolve, we can expect to see even more innovative applications of IoT Machine Learning across various sectors.

IEEE IoT MACHINE LEARNING PROJECTS ( 2024 – 2025 )

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Project CODE
TITLES
DOMAIN
SYNOPSIS
LINKS
1.   IEEE : IoT-Based Air Quality Monitoring System with Machine Learning for Accurate and Real-time Data Analysis IEEE IOT Machine Learning Title Title
2.  IEEE : Cloud Computing and IoT Based Intelligent Monitoring System for Photovoltaic Plants Using Machine Learning Techniques IEEE IOT Machine Learning Title Title
3. IEEE : Machine Learning-Based Network Vulnerability Analysis of Industrial Internet of Things IEEE IOT Machine Learning Title Title
4.  IEEE :PISIoT: A Machine Learning and IoT-Based Smart Health Platform for Overweight and Obesity Control IEEE IOT Machine Learning Title Title
5.  IEEE :E-Healthcare Monitoring System using IoT with Machine Learning Approaches IEEE IOT Machine Learning Title Title

IEEE EMBEDDED PROJECTS ( 2024 – 2025 )

Project CODE
TITLES
BASEPAPER
SYNOPSIS
LINKS
1. IEEE : Blind Aid Stick: Hurdle Recognition, Simulated Perception, Android Integrated Voice-Based Cooperation via GPS Along With Panic Alert System Title Title Title
2.  IEEE : Botnets and Internet of Things Security Title Title Title
3. IEEE : Child Safety Wearable Device Title Title Title
4.  IEEE :CityGuard: AWatchdog for Safety-Aware Conflict Detection in Smart Cities Title Title Title
5.  IEEE :Demo Abstract: Simulating Conflict Detection in Heterogeneous Services of a Smart City Title Title Title
6.  IEEE :Poster Abstract: Data-Centric IoT Services Provisioning in Fog-Cloud Computing Systems Title Title Title
7.  IEEE :After-the-Fact Leakage-Resilient Identity-Based Authenticated Key Exchange Title Title Title
8.  IEEE :An NFC featured three level authentication system for tenable transaction and abridgment of ATM card blocking intricacies Title Title Title
9.  IEEE :Self-Powered ZigBee Wireless Sensor Nodes for Railway Condition Monitoring Title Title Title
10.  IEEE :Towards Safer Roads through Cooperative Hazard Awareness and Avoidance in Connected Vehicles Title Title Title
11.  IEEE :A Provably Secure General Construction for Key Exchange Protocols Using Smart Card and Password* Title Title Title
12.  IEEE :IOT SENTINEL: Automated Device-Type Identification for Security Enforcement in IoT Title Title Title
13. IEEE :Wearable 2.0: Enabling Human-Cloud Integration in Next Generation Healthcare Systems Title Title Title
14. IEEE :The Internet of Things for South African Tourism Title Title Title
15. IEEE :Cloud Based Web Application Supporting Vehicle Toll Payment System Title Title Title
16. IEEE : HIVE: Home Automation Systemfor Intrusion Detection Title Title Title
17. IEEE : Fog Computing May Help to Save Energy in Cloud Computing Title Title Title
18. IEEE : Effective Ways to Use Internet of Things in the Field of Medical and Smart Health Care Title Title Title
19. IEEE : EyeSim: A Mobile Application for Visual-Assisted Wormhole Attack Detection in IoT-enabled WSNs Title Title Title
20. IEEE : A Capceptual Framework for IoT-based Healthcare System using Cloud Computing Title Title Title
21. IEEE : RISE: Role-based Internet of Things Service Environment Title Title Title
22. IJIRSET : Monitoring of School Kids Using Android Devices and Near Field Communication(NFC) Title Title Title
23. IEEE : The Internet of Things for Health Care: A Comprehensive Survey Title Title Title
24. IEEE : An IoT-Aware Architecture for Smart Healthcare Systems Title Title Title
25. IEEE : NFC Based Secure Mobile Healthcare System Title Title Title
26. IEEE : Smart Garbage Collection System in Residential Area Title Title Title

DHS Informatics believes in students’ stratification, we first brief the students about the technologies and type of IoT Machine Learning projects and other domain projects. After complete concept explanation of the IEEE IoT Machine Learning projects, students are allowed to choose more than one IEEE IoT Machine Learning projects for functionality details. Even students can pick one project topic from IoT Machine Learning and another two from other domains like IoT Machine Learning, image process, information forensic, big data, and IoT Machine Learning , block chain etc. DHS Informatics is a pioneer institute in Bangalore / Bengaluru; we are supporting project works for other institute all over India. We are the leading final year project centre in Bangalore / Bengaluru and having office in five different main locations Jayanagar, Yelahanka, Vijayanagar, RT Nagar & Indiranagar.

We allow the ECE, CSE, ISE final year students to use the lab and assist them in project development work; even we encourage students to get their own idea to develop their final year projects for their college submission.

DHS Informatics first train students on project related topics then students are entering into practical sessions. We have well equipped lab set-up, experienced faculties those who are working in our client projects and friendly student coordinator to assist the students in their college project works.

We appreciated by students for our Latest IEEE projects & concepts on final year IoT Machine Learning projects for ECE, CSE, and ISE departments.

Latest IEEE 2024 – 2025 projects on IoT Machine Learning with real time concepts which are implemented using Java, MATLAB, and NS2 with innovative ideas. Final year students of computer IoT Machine Learning, computer science, information science, electronics and communication can contact our corporate office located at Jayanagar, Bangalore for Embedded IoT project details.

IoT with Machine Learning Technology

IoT (Internet of Things) is an advanced automation and analytics system which exploits networking, sensing, big data, and artificial intelligence technology to deliver complete systems for a product or service. These systems allow greater transparency, control, and performance when applied to any industry or system.

IoT systems have applications across industries through their unique flexibility and ability to be suitable in any environment. They enhance data collection, automation, operations, and much more through smart devices and powerful enabling technology.

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.

Here we provided a IOT/INTERNET things 2024 – 2025 project list with abstract/ABSTRACT. IOT has been a very hot active during past few years and holds the potential as yet largely untapped to allow decision makers to track development progress using latest concepts.
Latest IOT/INTERNET topics,Latest IOT/INTERNET concept for diplomo,Engineering students,IOT/INTERNET project centers in Bangalore with high quality training and development.

IoT FEATURES

    The most important features of IoT include artificial intelligence, connectivity, sensors, active engagement, and small device use. A brief review of these features is given below :−
  • AI IoT essentially makes virtually anything “smart”, meaning it enhances every aspect of life with the power of data collection, artificial intelligence algorithms, and networks. This can mean something as simple as enhancing your refrigerator and cabinets to detect when milk and your favorite cereal run low, and to then place an order with your preferred grocer.
  • ConnectivityNew 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.
  • Sensors IoT loses its distinction without sensors. They act as defining instruments which transform IoT from a standard passive network of devices into an active system capable of real-world integration.
  • Active Engagement: Much of today’s interaction with connected technology occurs through passive engagement. IoT introduces a new paradigm for active engagement with content, products, or services.
  • 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.

DHS IOT (Internet of Things)
DHS IOT (Internet of Things)

IoT ADVANTAGE

    The advantages of IoT span across every area of lifestyle and business. Here is a list of some of the advantages that IoT has to offer :− Improved Customer Engagement Current analytics suffer from blind-spots and significant flaws in accuracy; and as noted, engagement remains passive. IoT completely transforms this to achieve richer and more effective engagement with audience.
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IoT 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.

    • Data CollectionThis software manages sensing, measurements, light data filtering, light data security, and aggregation of data. It uses certain protocols to aid sensors in connecting with real-time, machine-to-machine networks. Then it collects data from multiple devices and distributes it in accordance with settings. It also works in reverse by distributing data over devices. The system eventually transmits all collected data to a central server.
    • Device IntegrationSoftware supporting integration binds (dependent relationships) all system devices to create the body of the IoT system. It ensures the necessary cooperation and stable networking between devices. These applications are the defining software technology of the IoT network because without them, it is not an IoT system. They manage the various applications, protocols, and limitations of each device to allow communication.
    • Real-Time Analytics

These applications take data or input from various devices and convert it into viable actions or clear patterns for human analysis. They analyze information based on various settings and designs in order to perform automation-related tasks or provide the data required by industry.

  • Application and Process ExtensionThese applications extend the reach of existing systems and software to allow a wider, more effective system. They integrate predefined devices for specific purposes such as allowing certain mobile devices or engineering instruments access. It supports improved productivity and more accurate data collection.

IoT 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.

  • NFC and RFID: RFID (radio-frequency identification) and NFC (near-field communication) provide simple, low energy, and versatile options for identity and access tokens, connection bootstrapping, and payments
    • RFID technology employs 2-way radio transmitter-receivers to identify and track tags associated with objects.
    • NFC consists of communication protocols for electronic devices, typically a mobile device and a standard device.
  • Low-Energy Bluetooth: This technology supports the low-power, long-use need of IoT function while exploiting a standard technology with native support across systems.
  • Low-Energy Wireless: This technology replaces the most power hungry aspect of an IoT system. Though sensors and other elements can power down over long periods, communication links (i.e., wireless) must remain in listening mode. Low-energy wireless not only reduces consumption, but also extends the life of the device through less use.
  • Radio Protocols: ZigBee, Z-Wave, and Thread are radio protocols for creating low-rate private area networks. These technologies are low-power, but offer high throughput unlike many similar options. This increases the power of small local device networks without the typical costs.
  • LTE-A :  LTE-A, or LTE Advanced, delivers an important upgrade to LTE technology by increasing not only its coverage, but also reducing its latency and raising its throughput. It gives IoT a tremendous power through expanding its range, with its most significant applications being vehicle, UAV, and similar communication.
  • WiFi-Direct: WiFi-Direct eliminates the need for an access point. It allows P2P (peer-to-peer) connections with the speed of WiFi, but with lower latency. WiFi-Direct eliminates an element of a network that often bogs it down, and it does not compromise on speed or throughput.
DHS IOT (Internet of Things)

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