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Real-Time Cardiovascular Health Monitoring System Using IoT and Machine Learning Algorithms
Published in Vijayalakshmi Saravanan, Alagan Anpalagan, T. Poongodi, Firoz Khan, Securing IoT and Big Data, 2020
T. Vairam, S. Sarathambekai, K. Umamaheswari, R. Jothibanu, D. Manojkumar
Every object in a network is provided with a unique identification. An object can be a digital device, animal, human, and so on. When these are interconnected and transfer the information through the Internet, it is referred to as the IoT. M2M stands for Machine-to-machine communication, namely a machine connected with another machine by itself that does not require a human to be involved for further processing. M2M means connecting, managing, and collecting data from the cloud. M2M provides the IoT-enabled connectivity, which helps people to work smarter and to gain full control over their day-to-day activities. Devices and artefacts are linked to a network for the IoT, and its responsibility is to amalgamate information from the diverse devices and to share the meaningful information according to the application needs. The meaningful information is obtained by applying an analytics-based algorithm in the data that is received from the IoT devices.
A Review of Applications of Sensor Networks in Smart Agriculture
Published in Mohammad Ilyas, Sami S. Alwakeel, Mohammed M. Alwakeel, el-Hadi M. Aggoune, Sensor Networks for Sustainable Development, 2017
In its most basic form, M2M (Machine to Machine) involves devices that communicate independently, that is, without human intervention. Under M2M everyday objects are locatable, addressable, recognizable, readable, and controllable through the Internet (Ward 2012). In fact, M2M is now synonymous with the Internet of things (Anonymous 2010). Current advances in mobile technology have stretched Participatory Sensor Network (PSN) functionality to the level that making and receiving phone calls are considered rather rudimentary tasks. More and more mobile phones are now supplied with sensors (e.g., GPS, accelerometer, gyroscope, camera) and different types of connectivity mediums (bluetooth, wifi, GSM, etc.). This combination makes the mobile phone and in fact people carrying them a valuable source of gathering and transmitting data. A recent example of M2M is Zebra Net (Zhang et al. 2004) where the Zebras were tagged with wireless sensors, and the information was used for monitoring their activities, details in Section 1.5.3.
IoT and Blockchain
Published in E. Golden Julie, J. Jesu Vedha Nayahi, Noor Zaman Jhanjhi, Blockchain Technology, 2020
A. Mohana Priya, R. Malathi, S. Hemalatha, K. E. Kannammal
IoT has different perceptions with the combination of other technologies and applications. In this section, we see a new perception of IoT. Industrial IoT (IIoT) is the application of IoT technology in industrial settings with respect to instrumentation and control of sensors and devices that engage cloud technologies. Currently, industries have started using machine-to machine communication (M2M) to accomplish wireless automation and control. But with the materialization of cloud and associated technologies, which may include analytics and machine learning, industries can pull off a new automation layer and create new income and business strategies. IIoT is commonly called to be the fourth wave of industrial revolution or Industry 4.0.
Assessment framework for Proof of Concept (PoC) in Industry 4.0 – an interoperability approach
Published in International Journal of Computer Integrated Manufacturing, 2023
Luiz Felipe Pierin Ramos, Eduardo de Freitas Rocha Loures, Fernando Deschamps, André Luiz Alcântara Castilho Venâncio, Gabriel da Silva Serapião Leal
Despite being a relevant process, it is not allocated only in Brazil. The multinational has seen that the problem has gained significant proportions, when dealing with financial losses. In 2016 in Europe, an experiment was started to relieve the losses using IoT long-distance technology, also known LPWAN (Low Power Wide Area Network). This technology belongs to an M2M (Machine-to-Machine) communication type that may be defined as a ‘communication that takes place between machines (some objects and devices) with the capacity to interact without the need for human intervention’ (Kim et al. 2013). The main characteristics of an LPWAN are the low cost of the devices, low level of data transmission, long-distance communication in open areas, and low energy consumption (Wang and Fapojuwo 2017). Figure 10 shows the four pillars that support the use of this technology.
Modeling and Optimization of IoT Factors to Enhance Agile Manufacturing Strategy-based Production System Using SCM and RSM
Published in Smart Science, 2022
Umesh Kumar Vates, Bhupendra Prakash Sharma, Nand Jee Kanu, Eva Gupta, Gyanendra Kumar Singh
A flow chart is shown in to discuss the plan of the present investigation. To support the application domains, this tendency gives rise to intelligent, distributed, and self-organizing solutions. Industry 4.0 is implemented in three layers: the physical layer, the network layer, and the intelligent-application layer [41]. Machine-to-Machine (M2M) communication is the future of automation, and it is built on decentralized intelligence in which all machines can communicate with one another to arrive to independent or consensus inference. These decentralized intelligent solutions are critical to the digital revolution of industry 4.0. Compared to centralized solutions, decentralized alternatives offer more flexibility and quick decision support [42, 43]. To meet these important needs, new enabling solutions that support the applications must be investigated. Therefore, an initial investigation of this research shows a clear platform to evaluate the impact of identified IoT enablers at organizational, technological and employee level. This quantified approach using SCM and then RSM analysis will enhance the mind-set of the decision makers to develop and identify the suitable strategy for IoT-based smart agile manufacturing production systems on their shop floor.
Modelling IoT devices communication employing representative operation modes to reveal traffic generation characteristics
Published in International Journal of Parallel, Emergent and Distributed Systems, 2021
Basel Barakat, Simeon Keates, Ian J. Wassell, Kamran Arshad
For the previous two generations of wireless communications, the typical challenges were energy efficiency [3], data throughput [4,5], coverage [6] and end-to-end latency. For 5G, these issues are still considerably challenging; however, serving the expected number of connected devices might be overwhelming. The Internet of Things (IoT) is one of the leading forces in increasing the number of connected devices. The IoT can be defined as the network connecting billions of Machine-to-Machine communication (M2M) devices. M2M, also known as Machine-Type-Communications (MTC), is defined as the communication between machines or from machine to the network with little or no human intervention [7]. IoT is expected to play a crucial role in several sectors, including smart grids [8], environmental monitoring, surveillance, healthcare [9], and intelligent transport systems [10]. Several market studies have predicted that there will be more than 50 billion M2M devices in operation by 2020 [11]. Providing a ubiquitous service for this extraordinary number of connected devices and the consequent volume of data generated by those devices is the biggest challenges for network operators [12].