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Implementation of an IoT Based Intrusion Detection System for Smart City applications

Implementation of an IoT Based Intrusion Detection System fo...

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2024 International conference on Computational Intelligence for Green and Sustainable Technologies, ICCIGST 2024

作者： Lova Raju, K. Nishith Sai Sesha Kumar, K. Reginald, P.J. Sobha, D. Vignan's Foundation for Science Technology and Research Vadlamudi Department of Electronics and Communication Engineering Andhra Pradesh Guntur522213 India Vignan's Foundation for Science Technology and Research Vadlamudi Department of Advanced Computer Science and Engineering Andhra Pradesh Guntur522213 India

ISBN: (纸本)9798350381887

The occurrence of intrusions in smart cities has made the development of an inexpensive and effective intrusion detection system essential. Intrusion remains one of the most important aspects of smart city applications like homes, hospitals, transport, etc. Most of the existing systems employ focus only on one particular application like home security, not portable systems, and also use cameras only for surveillance. Therefore, taking into account the aforementioned drawbacks, this paper presents an intrusion system for smart city applications, leveraging Internet of Things (IoT) technology. The proposed system uses hardware components like Raspberry Pi model B+, Pi Camera, and PIR sensor (Passive Infrared) as well as software components like VNC viewer (Virtual Network Computing) and Thonny Python IDE (Integrated Development Environment). Motion detection is facilitated by the utilization of the PIR sensor, then the Pi Camera photographs the image automatically, and the Raspberry Pi device will send an alert via email to end-user devices that are connected with the email such as personal computers or smartphones. The captured data is securely stored in the email of the end-user's devices, ensuring confidentiality and privacy. © 2024 IEEE.

关键词： Network intrusion

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Increasing Order of Digital Filters of the Same Type in Robotic systems 12

Increasing Order of Digital Filters of the Same Type in Robo...

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12th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems: Technology and applications, IDAACS 2023

作者： Sytnikov, Tykhon Sytnikov, Valerii Streltsov, Oleh Stupen, Pavlo Odessa Polytechnic National University Odessa65044 Ukraine

ISBN: (纸本)9798350358056

Considering the issues of the filter order in a signal processing channel with sensors, through the serial link of the same type filters with low order. New approach to define cutoff frequency of such link was obtained. This solution allows quickly change the order and bandwidth of bandpass filters in robotic mobile platforms with limited computing resources. Proposed using a preliminary calculation of such frequencies, depending on the number of serial links of the same type of filters. This allows quickly rebuild the sensor signal processing channel. © 2023 IEEE.

关键词： AFC bandpass filters cutoff frequencies frequency-dependent components Industry 4.0-5.0 robotic systems serial link of components

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Simulation of Randomly Generated Domestic Environments for Assistive Robotics

Simulation of Randomly Generated Domestic Environments for A...

引用

International conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Fernandez, Noelia Espinoza, Gonzalo Mendez, Alberto Mora, Alicia Barber, Ramon Univ Carlos III Madrid RoboticsLab Syst Engn & Automat Madrid Spain

ISBN: (纸本)9798350352351;9798350352344

The need for solutions that ensure good quality of life in ageing populations have raised interest on assistance robots, which operate in domestic environments. Consequently, high level of comprehension of indoor conditions usually containing all sorts of obstacles, even dynamic, and the identification of particular objects or workspaces are often the main challenges for robot manipulation and navigation. However, realistic domestic indoors are hardly accessible or suitable for testing and it is very difficult for researchers to obtain physical models with the necessary characteristics. This article presents a novel approach for randomly generating simulation indoor domestic environments, with the ability to add more detail, customise rooms and easy to use. This enables its use in a wide range of applications such as creating domestic images datasets, object detection, instance segmentation and classification, robot navigation and manipulation. The proposed approach allows to compensate for the lack of multi-purpose domestic environments in simulation available online. The results obtained show a high percentage of successful of environment generation with a reduced execution time. Nevertheless, improvements can be made to reduce the high generation time and unsuccessful completions that high level of detail bring with it.

关键词： Simulation CoppeliaSim Domestic Environments Mobile Robots

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User-guided framework for scene generation using diffusion models

User-guided framework for scene generation using diffusion m...

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International conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Mendez, Alberto Prados, Adrian Fernandez, Noelia Espinoza, Gonzalo Barber, Ramon Univ Carlos III Madrid RoboticsLab Leganes Spain

ISBN: (纸本)9798350352351;9798350352344

In recent decades, one branch of robotics has focused on emulating specific human capabilities like manipulation, perception, and navigation to accomplish daily tasks. However, the human manner to solve these task extends beyond these conventional capabilities, including more complex faculties, such as imagination, which allows among other things to predict scenarios. This research introduces a novelty architecture designed to implement imaginative capacities in robots through the utilisation of Large Diffusion Models. The proposed framework comprises a perception stage, followed by a solution generation, and a final-stage selection algorithm. With this architecture the robot reach a reasoning able to imagine new situations with and without context, depending on the input information given. To achieve the best relation between performance and execution time, different diffusion models were systematically evaluated under a zero-shot configuration. Also, we make tests to prove the accuracy of the method and how useful users find this application. These were made for various scenes and different applications like rearrangement objects, setting the table for dinner or ordering a messy desktop.

关键词： diffusion model object detector prompt generation imagination user-guided

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Intelligent Fruit Quality Monitoring System using sensor Networks and Deep Learning

Intelligent Fruit Quality Monitoring System using Sensor Net...

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2024 International conference on Smart Electronics and Communication systems, ISENSE 2024

作者： Kumar, Arvind Jaya Krishna, N. Chandra, Mahesh Kumar, Rampravesh Sahoo, Jaya Prakash Poojitha, N. Karan, Biswajit Kishore, Kamlesh Gitam University Department of EECE Bengaluru India School of ECE Reva University Bengaluru India Sandip University Department of EEE Nashik India University of Stellenbosch Department of EEE Stellenbosch South Africa RTC Institute of Technology Department of ECE Bengaluru India

ISBN: (纸本)9798331528126

This paper presents a novel approach for fruit quality detection using a multi-modal system that combines sensor data and image processing techniques with deep learning. In the first stage of our experiment, we employed various sensors to measure temperature, gas levels, and moisture content using DHT 11 and MQ-135 sensors. These sensors provide valuable insights into the environmental conditions surrounding the fruits, which are crucial indicators of their freshness. In the second stage, we utilized image processing algorithms to pre-process fruit images and train a SqueezeNet convolutional neural network (CNN) to classify fruits into two classes: fresh and rotten. By integrating sensor data with image-based classification, our proposed method offers a comprehensive solution for real-time fruit quality assessment. Experimental results demonstrate the effectiveness of our approach in accurately detecting fruit quality, paving the way for advanced applications in food safety and quality control. © 2024 IEEE.

关键词： Convolutional neural networks

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Characterising an event-based detector for applications to wavefront sensing 9

Characterising an event-based detector for applications to w...

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conference on Adaptive Optics systems IX

作者： Cockram, Monique Rey, Noelia Martinez Australian Natl Univ Adv Instrumentat & Technol Ctr Res Sch Astron & Astrophys Canberra ACT Australia

ISBN: (纸本)9781510675186;9781510675179

Event-based sensors detect only changes in the brightness across a field of view, with each pixel producing an asynchronous stream of spatial-temporal events data, rather than recording frames of overall illumination of a scene like a traditional frame-based sensor. The location, timestamp, and polarity (positive or negative change) of the recorded events provides low bandwidth data that is useful in real-time sensing of changes in the field of view. These features result in advantages such as high temporal resolution, low latency, high dynamic range, and low power consumption. The use of these sensors has been explored in areas such as object tracking, robotics, and space situational awareness. We are proposing a new application of the event-based sensor in wavefront sensing for adaptive optics. At the advanced Instrumentation and Technology Centre (AITC) in the Australian National University (ANU), a test bench has been built to test this type of sensor. This study will present the results of this laboratory testing to characterise an event-based sensor's capabilities to detect tip-tilt aberrations in different conditions, such as background illumination levels. In particular, the event-based sensor's immunity to a constant background illumination was investigated by introducing an external light source into the scene and recording its performance for different signal strengths. We will present the results of the bench testing, the error budget for tip-tilt sensing using these event-based detectors, and a characterisation of the response of event-based sensors to different illumination conditions.

关键词： event-based detectors tip-tilt adaptive optics

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Distributed Fiber Optic sensors for applications in Electric Arc Furnaces 3

Distributed Fiber Optic Sensors for Applications in Electric...

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conference on Optical Waveguide and Laser sensors iii

作者： Inalegwu, Ogbole C. Saha, Rony Kumer Mekala, Yeshwanth Reddy Mumtaz, Farhan O'Malley, Ronald J. Gerald, Rex E., II Huang, Jie Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO 65409 USA Missouri Univ Sci & Technol Dept Mat Sci & Engn Rolla MO 65409 USA Missouri Univ Sci & Technol Peaslee Steel Mfg Res Ctr PSMRC Rolla MO 65409 USA

ISBN: (纸本)9781510674073;9781510674066

This study presents the application of three distinct fiber optic sensor (FOS) technologies for temperature monitoring during Electric Arc Furnace (EAF) operations. This work looks into the application of fiber Bragg grating (FBG), Brillouin-based, and Rayleigh-based distributed FOS technologies. Through the deployment of these sensors in steel mills, we have successfully achieved distributed temperature monitoring within the bottom anode and side walls of the EAF. Our approach involves data collection from mock foundry trials and real-world EAF operations in a steel mill. The real-time temperature monitoring of the EAF's bottom anode provides insights for early detection of temperature anomalies in the refractory layer, while the monitoring of the side wall is primarily for pinpointing hotspots within the furnace wall for effective and efficient water-spray cooling. The integration of these advanced FOS technologies brings forth a transformative solution for the steel-making industry. By providing real-time, distributed temperature profiles and enabling proactive anomaly detection, our work contributes to enhanced operational efficiency and, more critically, improved safety in EAF facilities. This research not only showcases the potential of FOS applications but also demonstrates their ability to facilitate timely interventions in the high-temperature, high-stress environment of EAFs, ultimately bolstering overall steel production and safety standards in steel mills.

关键词： steel-making high-temperature electric arc furnace fiber optic sensors Rayleigh scattering Brillouin scattering fiber Bragg grating

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advanced Camouflage Robot for Military Spying applications using sensor Fusion and Machine Learning 3

Advanced Camouflage Robot for Military Spying Applications u...

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3rd IEEE International conference on Blockchain and Distributed systems Security, ICBDS 2024

作者： Kulkarni, Neeraj P Khan, Subim N. Rathod, Rahul Ramkishan Choure, Ajay Raosaheb Chinchole, Mahesh Gokul Jspm Rajarshi Shahu College of Engineering Tathawade Pune India Soet D Y Patil University Ambi Pune India Bhivarabai Sawant Institute Of Technology And Research E&tc Department Wagholi Pune India Nutan Maharashtra Institute of Engineering and Technology E&tc Department Pune India

ISBN: (纸本)9798350354348

The current defense application scenario. the ability to blend into the environment is crucial for reducing detection and enhancing operational efficiency. This paper presents the development of an advanced camouflage robot to dynamically adapt its color to match its surroundings. The proposed system utilizes a combination of machine learning, computer vision, and sensor fusion to achieve camouflaging using the RGB LED panels mounted on the robot to adapt to the color of the surroundings. The robot is equipped with a video camera system that captures real-time video feed of the environment. The captured video is then processed by a trained machine learning model, which analyzes the color distribution in the surroundings. Simultaneously, the robot uses RGB color sensors to accurately detect the colors present in its immediate vicinity. The data from both the camera and the sensors are integrated to determine the predominant color around the robot. The hybrid camouflaging approach involves feeding the combined data into the machine learning model, which then calculates the color of maximum distribution. The robot then activates its RGB panels, adjusting their color to blend with the identified predominant color in the environment thereby making it difficult to locate. This process allows the robot to effectively camouflage itself, minimizing its visual footprint. KNN and sensor fusion techniques are used to achieve this task. © 2024 IEEE.

关键词： Nearest neighbor search

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Optimizing Service Replication and Placement for IoT applications in Fog Computing systems 30th

Optimizing Service Replication and Placement for IoT Applica...

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30th European conference on Parallel and Distributed Processing (Euro-Par)

作者： Ait-Salaht, Farah Rebai, Maher Izri, Nora Leonard de Vinci Pole Univ Res Ctr F-92916 Courbevoie France

ISBN: (纸本)9783031695766;9783031695773

Fog Computing extends Cloud Computing to the network edge, enhancing distributed computing to meet the growing needs of Internet of Things (IoT) applications requiring real-time or near-real-time analysis. This research focuses on efficiently managing the vast amounts of data generated by IoT devices and the continuous data streams they produce, employing an advanced replication and placement strategy for application components across distributed Fog Computing nodes. This approach enables scalable and parallel data processing to adapt to demand fluctuations, prevent over-provisioning, and maintain low response times, making it particularly effective for the dynamic nature of data stream processing in IoT applications. In this paper, we propose an Optimal IoT Service Replication and Placement (SRP) model, formulated as a constraint satisfaction problem, that considers the diverse requirements of IoT applications and the available infrastructure resources. Our model is designed to be adaptive and extensible, addressing the challenge of workload variability through real-time optimization. Numerical evaluations confirm the superior performance and scalability of our model over existing methods, while maintaining quality of service constraints. This highlights the potential of our approach to improve efficiency and resource management in Fog Computing environments.

关键词： Fog Computing Service replication Service placement IoT applications Constraint Programming

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sensor Automation for Industrial applications and Prediction of Energy Level for Home Appliances Using Machine Learning Algorithm 9

Sensor Automation for Industrial Applications and Prediction...

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9th International conference on advanced Computing and Communication systems, ICACCS 2023

作者： Duraisamy, Premkumar Natarajan, Yuvaraj Selvakumari Jeya, I Jasmine Niranjani, V. KPR Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Hindusthan College of Engineering and Technology Department of Information Technology Coimbatore India Sri Eshwar College of Engineering Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350397376

In recent years wireless sensor networks have helped with automation in many industry domains. Wireless technology cuts cable costs, deployment time and information to transfer and process from source to destination. To make good intelligent and highly automated systems, sensors are crucial. They make it possible to detect, analyze, measure, and process a variety of alterations that occur in industrial equipment's location, length, height, appearance, displacement, etc. This paper described the industrial standardization of different WSN protocols like Zig-Bee, Wireless HART, UWB, IETF 6LowPAN, ISA100, Bluetooth and Wi-Fi. The work represented a few applications of WSNs in industry and its implementation challenges like safety, security, and availability. The work collected the energy consumption data of different home appliances. We applied the LightGBM machine learning algorithm to find a better energy consumption and prediction result. © 2023 IEEE.

关键词： Energy utilization

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