An Open Source Extensible Smart Energy Framework

A systematic survey of Internet of Things frameworks for smart city applications

Internet of Things, cognitive systems, and blockchain technology are three fields which have created numerous revolutions in software development. It seems that a combination among these fields may results in emerging a high potential and interesting field. Therefore, in this paper, we propose a framework for Internet of Things based on cognitive systems and blockchain technology. To the best of our knowledge, there is no framework for Internet of Things based on cognitive systems and blockchain. In order to study the applicability of the proposed framework, a recommender system based on the proposed framework is suggested. Since the proposed framework is novel, the suggested recommender system is novel. The suggested recommender system is compared with the existing recommender systems. The results show that the suggested recommender system has several benefits which are not available in the existing recommender systems.

Internet of things (IoT) paradigm is becoming ubiquitous in everyday life. IoT-based systems are increasingly getting deployed in generic household, healthcare, public utilities, etc., related application. The reason for such rapid acceptance is in majority due to the internet's feature of connect from anywhere. However, due to some weaknesses inherent with the internet itself, IoT deployments also face certain challenges. Though there is a growing number of IoT-related reference architectures, frameworks, guidelines, platforms and standards, majority of them are yet to address the concerns due to internet outage. Furthermore, such growing numbers of architectures, frameworks, etc., also means bountiful amounts of both opportunities and risks for IoT vendors and original equipment manufacturers (OEMs). Of course, the IoT-device consumers also run the risks if the purchased products frameworks incompatible. We present One IoT version 2 (v2), an IoT framework and protocol that addresses the internet outage scenario. Similar to version 1 (v1), One IoT v2 is also forward compatible.

Internet of Things (IoT) represent a network of resource‐constrained sensor devices connected through the open Internet, susceptible to misuse by intruders. Traditional standalone intrusion detection systems (IDS) are tasked with monitoring device behaviours to identify malicious activities. These systems not only require extensive network and system resources but also cause delays in detecting a malicious actor due to unavailability of a comprehensive view of the intruder's activities. Collaboration among IoT devices enables considering knowledge from a collection of host and network devices to achieve improved detection accuracy in a timely manner. However, collaboration introduces the challenge of energy efficiency and event processing which is particularly significant for resource‐constrained devices. In this paper, we present a collaborative intrusion detection framework (COLIDE) for IoT leveraging collaboration among resource‐constrained sensor and border nodes for effective and timely detection of intruders. The paper presents a detailed formal description of the proposed framework along with analysis to assess its effectiveness for a typical IoT system. We implemented the COLIDE framework with Contiki OS and conducted thorough experimentation to evaluate its performance. The evaluation demonstrates efficiency of COLIDE framework with respect to energy and processing overheads achieving effectiveness within an IoT system.

The purpose of this paper is to introduce a technology-oriented SCM (Supply Chain Management) development methodology, which can be used in the design of IoT (Internet of Things) frameworks especially characterized by supply chain processes. In order to meet DSC (Digital Supply Chain) expectations, two areas are examined in detail during the literature review. Firstly, the current SCM models are studied. Secondly, Industry 4.0 requirements had to be surveyed. As a consequence, challenges and gaps are identified for which we seek the solution during our research. Based on the results, it can be stated that digitization has definitely required an improved technological solution that IoT frameworks can provide. The result is a technology-driven, IoT-based SCM development methodology that serves as a basis for the design of such platforms, which will manage supply chains. To prove the feasibility of the proposed development methodology, the Arrowhead industrial IoT framework is used for validation.

The 21st century has seen rapid changes in technology, industry, and social patterns. Most industries have moved towards automation, and human intervention has decreased, which has led to a revolution in industries, named the fourth industrial revolution (Industry 4.0). Industry 4.0 or the fourth industrial revolution (IR 4.0) relies heavily on the Internet of Things (IoT) and wireless sensor networks (WSN). IoT and WSN are used in various control systems, including environmental monitoring, home automation, and chemical/biological attack detection. IoT devices and applications are used to process extracted data from WSN devices and transmit them to remote locations. This systematic literature review offers a wide range of information on Industry 4.0, finds research gaps, and recommends future directions. Seven research questions are addressed in this article: (i) What are the contributions of WSN in IR 4.0? (ii) What are the contributions of IoT in IR 4.0? (iii) What are the types of WSN coverage areas for IR 4.0? (iv) What are the major types of network intruders in WSN and IoT systems? (v) What are the prominent network security attacks in WSN and IoT? (vi) What are the significant issues in IoT and WSN frameworks? and (vii) What are the limitations and research gaps in the existing work? This study mainly focuses on research solutions and new techniques to automate Industry 4.0. In this research, we analyzed over 130 articles from 2014 until 2021. This paper covers several aspects of Industry 4.0, from the designing phase to security needs, from the deployment stage to the classification of the network, the difficulties, challenges, and future directions.

The rapidly development in the devices technology as well in the communication technology offers the facilities to development the electronics system. Data acquisition system is the most electronics system which is used in the large area of application i.e process parameter monitoring in industry, health monitoring, and water monitoring. Recently there is a requirement to do the long distance monitoring. Therefore remote monitoring based on web which is known as internet of things (IoT) framework is a choice. In this work has been designed an implemented a data acquisition system based on internet of things framework. The system used a raspberry Pi as processor. It offers a small dimension and portable system. The data monitoring is possible by web browser and can be access via web browser devices i.e computer, laptop, or smart mobile phone.

The Internet of things (IoT) ecosystem has grown exponentially with the convergence of various technologies such as deep learning, sensor systems, and advances in computing platforms. With such a highly pervasive nature of “smart” devices, the nature of data being collected and processed can be increasingly private and require safeguards to ensure the data’s integrity and security. Physically unclonable functions (PUFs) have emerged as a lightweight, viable security protocol in the Internet of Things (IoT) framework. Malicious modeling of PUF architectures has proven to be difficult due to the inherently stochastic nature of PUF architectures. In this work, we show that knowledge of the underlying PUF structure is unnecessary to clone a PUF. We tackle the problem of cloning PUF-based edge nodes in different settings such as unencrypted, encrypted, and obfuscated challenges in an IoT framework. We present a novel non-invasive, architecture-independent, machine learning attack for robust PUF designs and can handle encryption and obfuscation-based security measures on the transmitted challenge response pairs (CRPs). We show that the proposed framework can successfully clone different PUF architectures, including those encrypted using two (2) different encryption protocols in DES and AES and with varying degrees of obfuscation. We also show that the proposed approach outperforms a two-stage brute force attack model. Finally, we offer a machine learning-based countermeasure, a discriminator, which can distinguish cloned PUF devices and authentic PUFs with an average accuracy of 96%. The proposed discriminator can be used for rapidly authenticating millions of IoT nodes remotely from the cloud server.

According to the American Academy of Sleep Medicine (AASM), patients with apnea of 10 seconds or more , and more than 5 times per hour can be diagnosed with sleep disorders. The current gold standard for detecting this type of people with sleep disorder is Polysomnography (PSG). But more than 80% Obstructive Sleep Apnea(OSA) patients of the Sleep Disorder(SD) have not been detected. The reason is that the current configuration of PSG is insufficient in more than 2,500 sleep labs in the United States , and that the lack of manpower of sleep professional technicians who analyze PSG signal has caused many OSA patients to be diagnosed in a timely and effective manner. It is no effective measures to reduce the risk even after OSA patients have been diagnosed. Current medical treatments are either surgical or a lifelong Continuous positive dual channel air pressure ventilator(CPAP). Domestic research shows that OSA patients have poor sleep at night and sleepiness during the day. It often results in inefficient work and causes many traffic accidents. Therefore, how to take effective monitoring measures for these already diagnosed OSA patients has become an urgent problem to be solved.This paper extracts an interactive monitoring system for patients with OSA based on the Internet of Things(IoT) framework. It can reduce the timely rescue of OSA patients when they are in danger in field operations. At the same time, through the interactive function of this indicator mark, the anxiety during the waiting process can be reduced. It is also convenient for the peers to report the progress of the patient in time. The specific method is to use the existing IoT framework. The IoT data acquisition layer uses wearable sensors to collect vital signs of patients, with emphasis on ECG and SpO2 signals. The network layer transmits the collected physiological signals to the Beidou indicator using the Bluetooth Low Energy (BLE) protocol. The platform layer adopts the mature rescue interaction platform of Beidou&GPS. The previous GPS indicator has no short message function, and the patient can only passively wait for rescue. Positional standard is improved through Beidou model, and the short message interaction function has been added. Then the patient can report the progress of the disease in time while waiting for the rescue. After our simulation test, the effectiveness of the OSA patient rescue monitoring system based on the IoT framework has been greatly improved, especially in outdoor work, where the mobile phone signal coverage is relatively weak. The short message function added by the Beidou indicator can be used to provide timely progress of the patient's condition, and provide the medical rescue team with the data support to offer a more accurate rescue plan. After a comparative trial, the rescue rate of the OSA patients with the detection device of this article increased by 10 percentage points compared with the rescue rate with only GPS satellite phones.

Internet of Things (IoT) is one of the significant technologies, which interconnects and interrelate computing objects that transforms the information over the network. The digital and physical world is merged together and enables the communication with real time data. Nowadays, it is comprehensively affecting daily activities of human in both academic and industrial domains. Moreover, it aims to create a new intelligent era of IoT by integrating the smart objects with physical objects. However, IoT undergoes various challenging security issues, such as complexity of environment, constrained resources, scalability etc. To overcome these issues, many researchers developed efficient security solutions in various IoT frameworks, which focuses on ease of development, deployment and maintenance of IoT applications. In this paper, an IoT framework is mainly targeting to simplify the IoT application implementation and emphasizes the security mechanisms related to authentication, authorization, confidentiality, non-repudiation, privacy and availability. Moreover, the proposed framework named as Framework for Secure IoT Environment (FSIE) is compared with security architectures of AWS IoT, Azure IoT suite, Brillo/Weave (three) IoT frameworks. The comparative analysis is done by taking five parameters, which are computational complexity, communication complexity, mobility, scalability and quality of service. The new framework FSIE is providing security and privacy in terms of scalability and flexibility. It is also proved that it is more efficient than the other frameworks chosen.

This article details the development and deployment of a wireless Internet of Things (IoT) framework designed for monitoring the status of traction motor drives in electric vehicles (EVs). The construction and experimental validation of a prototype, which utilizes an ESP8266 microcontroller to gather data on motor vibration, current, and temperature for motor condition assessment, are explored. The IoT infrastructure has been crafted utilizing readily available commercial components and an open-source software ecosystem, ensuring efficient and robust data collection with minimal energy usage. The data procured by the IoT framework is transmitted to a cloud-based server instantaneously. Trial outcomes indicate the system's proficiency in capturing critical motor parameters, uploading them to the cloud, and issuing instant alerts to operators upon the detection of any motor irregularities. Leveraging IoT advancements allows for proactive and remote planning of traction motor maintenance, bolstered by comprehensive data acquisition and analytical processes. Moreover, the implementation of innovative energy-saving measures ensures that the sensor node's battery consumption is markedly low, making it an ideal choice for mobile applications.

A Framework of Energy Consumption Modelling for Additive Manufacturing Using Internet of Things

Physically Unclonable Functions (PUFs) have emerged as a lightweight, viable security protocol in the Internet of Things (IoT) framework. While there have been recent works on crypt-analysis of PUF-based models, they require physical access to the device and knowledge of the underlying architecture along with unlimited access to the challenge-response pairs in plain text without encryption. In this work, we are the first to tackle the problem of encrypted PUF-based authentication in an IoT framework. We propose a novel, generative framework based on variational autoencoders that is PUF architecture-independent and can handle encryption protocols on the transmitted CRPs. We show that the proposed framework can successfully clone three (3) different PUF architectures encrypted using two (2) different encryption protocols in DES and AES. We also show that the proposed approach outperforms a brute-force machine learning-based attack model by over \(20\%\).

Duties are segregated within a team by using the role-based access control (RBAC) in the Azure Internet of Things (IoT) framework, and only an appropriate level of access is granted to users to perform specific tasks, depending on a given situation. However, the same authentication and authorization mechanism is used for "sort of user," which increases the operation overload on the cloud server. Moreover, due to its RBAC nature, the IoT framework is inefficient in handling a dynamic situation where multiple users request similar kinds of resources, by creating several repeated roles. This results in inconsistent and inflexible implementation and the loss of the capability to efficiently address policy management, semantics, redundancy issues in roles, dynamic user handling, work delegation issues, scalability, role explosion, individual rights, and security issues in large organizations. In this article, we designed and presented a novel access control model for a significantly large medical scenario with efficient priority-based authentication mechanisms to address the abovementioned problems associated with the Azure IoT cloud. The proposed model encapsulates the enforcement of priority-based resource access rights across multiple users in a large organization, reduces inefficiency and ineffectuality, and supports individuals with the consistent implementation of policies. We evaluated the benefits of the proposed model by comparing it with existing models and the Azure model, using the healthcare use-case situation. The comparison results show that by incorporating the priority attribute facility in the existing RBAC model, the proposed model classifies the policy mechanism based on priority attributes and proves that the proposed model is capable of handling problems that generally occur when dealing with huge dynamic scenarios in large organizations.

Remote correspondence frameworks are exceedingly disposed to security perils. The critical usages of remote correspondence frameworks are in military, business, human administrations, retail, and transportations. These structures use wired, cell, or ad hoc frameworks. Remote sensor frameworks, actuator frameworks, and vehicular frameworks have gotten a fantastic thought in the open eye and industry. Of late, the Internet of things (IoT) has become broad research thought. The IoT is considered as possible destiny of the Web. In future, IoT will accept a vital activity and change our living styles, standards, similarly to game plans. The use of IoT in different applications is required to rise rapidly in the coming years. The IoT grants billions of devices, society, and organizations to connect with others and exchange information. Due to the extended usage of IoT contraptions, the IoT frameworks are slanted to various security strikes. The presence of successful security and assurance shows that IoT frameworks are incredibly expected to ensure protection, get the chance to control, and decency, among others. In this chapter, a complete assessment on security and insurance issues in IoT frameworks is provided.