scholarly journals The Device–Object Pairing Problem: Matching IoT Devices with Video Objects in a Multi-Camera Environment

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5518
Author(s):  
Kit-Lun Tong ◽  
Kun-Ru Wu ◽  
Yu-Chee Tseng

IoT technologies enable millions of devices to transmit their sensor data to the external world. The device–object pairing problem arises when a group of Internet of Things is concurrently tracked by cameras and sensors. While cameras view these things as visual “objects”, these things which are equipped with “sensing devices” also continuously report their status. The challenge is that when visualizing these things on videos, their status needs to be placed properly on the screen. This requires correctly pairing visual objects with their sensing devices. There are many real-life examples. Recognizing a vehicle in videos does not imply that we can read its pedometer and fuel meter inside. Recognizing a pet on screen does not mean that we can correctly read its necklace data. In more critical ICU environments, visualizing all patients and showing their physiological signals on screen would greatly relieve nurses’ burdens. The barrier behind this is that the camera may see an object but not be able to see its carried device, not to mention its sensor readings. This paper addresses the device–object pairing problem and presents a multi-camera, multi-IoT device system that enables visualizing a group of people together with their wearable devices’ data and demonstrating the ability to recover the missing bounding box.

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4034
Author(s):  
Arie Haenel ◽  
Yoram Haddad ◽  
Maryline Laurent ◽  
Zonghua Zhang

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.


2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Mihui Kim ◽  
Mihir Asthana ◽  
Siddhartha Bhargava ◽  
Kartik Krishnan Iyyer ◽  
Rohan Tangadpalliwar ◽  
...  

The increasing number of Internet of Things (IoT) devices with various sensors has resulted in a focus on Cloud-based sensing-as-a-service (CSaaS) as a new value-added service, for example, providing temperature-sensing data via a cloud computing system. However, the industry encounters various challenges in the dynamic provisioning of on-demand CSaaS on diverse sensor networks. We require a system that will provide users with standardized access to various sensor networks and a level of abstraction that hides the underlying complexity. In this study, we aim to develop a cloud-based solution to address the challenges mentioned earlier. Our solution, SenseCloud, includes asensor virtualizationmechanism that interfaces with diverse sensor networks, amultitenancymechanism that grants multiple users access to virtualized sensor networks while sharing the same underlying infrastructure, and adynamic provisioningmechanism to allow the users to leverage the vast pool of resources on demand and on a pay-per-use basis. We implement a prototype of SenseCloud by using real sensors and verify the feasibility of our system and its performance. SenseCloud bridges the gap between sensor providers and sensor data consumers who wish to utilize sensor data.


Author(s):  
Yong Kyu Lee

This chapter reviews the internet of things (IoT) as a key component of a smart city and how it is applied to consumers' daily lives and business. The IoT is a part of information and communication technology (ICT) and is considered a powerful means to improve consumers' quality of life. The “thing” could be any object which has internet capability, such as wearable devices and smart TVs/phones/speakers. Several studies have identified driving factors that have led consumers to adopting them, but also concerns of consumers' resistance to IoT devices. The three major fields of application of IoT technologies were selected to review the role of the IoT in consumers' daily lives and business.


2019 ◽  
Vol 11 (5) ◽  
pp. 102
Author(s):  
Gaël Vila ◽  
Christelle Godin ◽  
Oumayma Sakri ◽  
Etienne Labyt ◽  
Audrey Vidal ◽  
...  

This article addresses the question of passengers’ experience through different transport modes. It presents the main results of a pilot study, for which stress levels experienced by a traveller were assessed and predicted over two long journeys. Accelerometer measures and several physiological signals (electrodermal activity, blood volume pulse and skin temperature) were recorded using a smart wristband while travelling from Grenoble to Bilbao. Based on user’s feedback, three events of high stress and one period of moderate activity with low stress were identified offline. Over these periods, feature extraction and machine learning were performed from the collected sensor data to build a personalized regressive model, with user’s stress levels as output. A smartphone application has been developed on its basis, in order to record and visualize a timely estimated stress level using traveler’s physiological signals. This setting was put on test during another travel from Grenoble to Brussels, where the same user’s stress levels were predicted in real time by the smartphone application. The number of correctly classified stress-less time windows ranged from 92.6% to 100%, depending on participant’s level of activity. By design, this study represents a first step for real-life, ambulatory monitoring of passenger’s stress while travelling.


2021 ◽  
Vol 13 (8) ◽  
pp. 210 ◽  
Author(s):  
Sheetal Ghorpade ◽  
Marco Zennaro ◽  
Bharat Chaudhari

With exponential growth in the deployment of Internet of Things (IoT) devices, many new innovative and real-life applications are being developed. IoT supports such applications with the help of resource-constrained fixed as well as mobile nodes. These nodes can be placed in anything from vehicles to the human body to smart homes to smart factories. Mobility of the nodes enhances the network coverage and connectivity. One of the crucial requirements in IoT systems is the accurate and fast localization of its nodes with high energy efficiency and low cost. The localization process has several challenges. These challenges keep changing depending on the location and movement of nodes such as outdoor, indoor, with or without obstacles and so on. The performance of localization techniques greatly depends on the scenarios and conditions from which the nodes are traversing. Precise localization of nodes is very much required in many unique applications. Although several localization techniques and algorithms are available, there are still many challenges for the precise and efficient localization of the nodes. This paper classifies and discusses various state-of-the-art techniques proposed for IoT node localization in detail. It includes the different approaches such as centralized, distributed, iterative, ranged based, range free, device-based, device-free and their subtypes. Furthermore, the different performance metrics that can be used for localization, comparison of the different techniques, some prominent applications in smart cities and future directions are also covered.


Author(s):  
Tanishka and Prof. Shikha Gupta

The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Internet of Things (IoT) is rapidly gaining momentum in the scenario of telecommunications. Conventional networks allow for interactivity and data exchange, but these networks have not been designed for the new features and functions of IoT devices. In this paper, an algorithm is proposed to share common recourse among Things, that is, between different types of smart appliances. . Purpose is to analyze deeper the cases separating the network and IoT layout, giving a deeper explanation of the purpose of the simulations, presenting all the information needed to utilize the exercises but also giving suggestion how to expand the exercises further. This implementation can be implemented effectively using package tracking software that includes IoT functions to control and simulate a smart home. IoT technology can be applied to many real life issues, such as: homework, treatment, campus, office, etc.


2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Jie Xu

The Narrow Band-Internet of Things (NB-IoT) is a wideband radio technology developed for the Internet of Things that enables smoother- and farther-reaching connectivity between IoT devices. In addition to traditional network optimization devices, Bluetooth and Wi-Fi, its virtue is low cost, and it consumes less energy and has high coverage and extended battery life. In order to secure the balance of task execution latency across NB-IoT devices, in this research work, we design a handheld NB-IoT wireless communication device. Furthermore, we provide realistic resource-sharing methods between multimedia and sensor data in NB-IoT wireless deployment by our accurate analytical methodology. In addition, we have considerably enhanced technology for gathering Big Data from several scattered sources, in combination with advancements in big data processing methodologies. The proposed handheld terminal has a wide variety of commercial applications in intelligent manufacturing and smart parking. Simulation outcomes illustrate the benefits of our handheld terminal, which provides practical solutions for network optimization, improving market share and penetration rate.


2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
JeongGil Ko ◽  
Byung-Bog Lee ◽  
Kyesun Lee ◽  
Sang Gi Hong ◽  
Naesoo Kim ◽  
...  

The vision of theInternet of Things (IoT)is coming closer to reality as a large number of embedded devices are introduced to our everyday environments. For many commercial IoT devices, ubiquitously connected mobile platforms can provide global connectivity and enable various applications. Nevertheless, the types of IoT resource-utilizing applications are still limited due to the traditional stovepipe software architecture, where the vendors provide supporting software on an end-to-end basis. This paper tries to address this issue by introducing theSensor Virtualization Module (SVM), which provides a software abstraction for external IoT objects and allows applications to easily utilize various IoT resources through open APIs. We implement the SVM on both Android and iOS and show that the SVM architecture can lead to easy development of applications. We envision that this simplification in application development will catalyze the development of various IoT services.


With advancement in smart home services on mobile and wearable devices, individual can smartly control his/her home appliances such as fan, refrigerator, TV, air conditioner, etc., in an efficient manner. Internets of Things (IoT) devices are extensively utilized to interchange the data between smart applications, mobiles, and wearables. IoT devices are responsible for monitoring and sensing the data about home appliances with the help of sensor nodes, the obtained data is then communicate to given high-end devices for taking the suitable action. The overall objective of this paper is to study the existing IoT analytics techniques which are used to build smart applications for homes. This paper also discusses the various challenges to design a suitable smart home using IoTs. Thereafter, a comparative analyzes are considered to evaluate the shortcomings of these techniques and various gaps are formulated in the existing techniques. Finally, a methdology has been devised which can overcome the shortcomings of existing models and help enhancing the functioning of human activity recognition in smart homes.


Author(s):  
Hussam Ali Alothman ◽  
Mohammad T. Khasawneh ◽  
Nagen N. Nagarur

Internet of things or IoT represents an emerging concept where the objects and humans are identifiable, connected and can communicate over the internet or the wireless world. With IoT, everything can communicate anytime and at anyplace. IoT has many applications and one of the most important applications is the manufacturing. The IoT in industry sector, sometimes referred to as IIoT, is considered to be a very important factor in the introduction of the fourth industrial revolution. Major manufacturing powers around the world are already trying to adopt IoT in their production systems and lead the way in this new era of advanced manufacturing. A huge number of IoT devices are already being used and connected and it is expected that the number of these applications and devices will increase dramatically in the next few years. In this work, an overview of IoT in manufacturing will be presented. This includes a discussion of some of the advantages and benefits of adopting IoT in manufacturing in addition to the issues and challenges that accompany this IoT application. The discussion will also include the concept of smart manufacturing, how production processes and other related activities can be connected in real time and how this can be achieved by adopting IoT in manufacturing. Furthermore, the enabling technologies needed to realize IoT (whether it is to be applied in a new plant or in already existing machines that don’t have IoT capabilities) are shown along with the different layers or phases needed for this IoT adoption. Finally, some real life examples of factories that adopted IoT are shown.


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