Middleware for Internet of Things: Survey and Challenges

Chelloug, Samia Allaoua; El-Zawawy, Mohamed A.

doi:10.1080/10798587.2017.1290328

Cited by 20 publications

(10 citation statements)

References 30 publications

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“…Application examples for commonly used technologies in terms of middleware types are Wireless Sensor Networks (WSN) (Akerberg, Gidlund & Björkman, 2011), Radio Frequency Identification (RFID) (Bartneck, Klaas, Schoenherr, & Siemens, 2009), Machine-to-Machine (M2M) communication (Fang et al, 2014), and Supervisory Control and Data Acquisition (SCADA) systems (Strasser,Ebenhofer,Sünder,& Valentini,0000). Middleware should aim to ease the development of new applications and enable integration of heterogeneous computing and communication devices supporting interoperability (Chelloug & El-Zawawy, 2017). Current challenges are driven by functional requirements (for example, code management and event management), nonfunctional requirements (for example, scalability, real-time, reliability, security and privacy or ease of deployment) and architectural requirements (for example, programming abstraction, interoperability, service-based, adaptive and context-awareness).…”

Section: Information and Communication Technologymentioning

confidence: 99%

Innovation landscape and challenges of smart technologies and systems – a European perspective

Micheler

Goh

Lohse

2019

Production & Manufacturing Research

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Smart technologies with higher degrees of autonomy will be essential to achieve the next breakthrough in both agility and productivity in future manufacturing systems, often referred to as Industry 4.0. However, the technologies will also bring substantial design and integration challenges and novelty risks to manufacturing businesses. The aim of this paper is to analyse the current landscape and to identify the challenges for introducing smart technologies into manufacturing systems in Europe. Expert knowledge from both industrial and academic practitioners in the field was extracted using an online survey. A workshop was used to triangulate and extend the survey results. The findings indicate three main challenges for the ubiquitous implementation of smart technologies in manufacturing are: i) the perceived risk of novel technologies, ii) the complexity of integration, and iii) the consideration of human factors. Recommendations are made based on these findings to transform the landscape for smart manufacturing. ARTICLE HISTORY

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Section: Information and Communication Technologymentioning

confidence: 99%

Innovation landscape and challenges of smart technologies and systems – a European perspective

Micheler

Goh

Lohse

2019

Production & Manufacturing Research

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“…The smart city consists of various smart applications or makes device smart in the city such as smart agriculture, smart parking, smart house, monitoring the climate environment, smart building, smart traffic and transportation systems and etc. [4,5].…”

Section: Introductionmentioning

confidence: 99%

Faulty sensor detection using multi-variate sensors in internet of things (IoTs)

Omar

Malik

Jamil

et al. 2020

IJEECS

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IoT devices are lightweight and have limited computational capabilities often exposed to harsh environments, which can cause failure on the IoT devices [1, 2]. The failure on the IoT devices is also caused due to limited battery life, hardware failure or human mistakes. Sensor faults can be categorized under one type of hardware failure, such as sensor burn, reduced sensor sensitivity and malfunctioned sensors. Any faulty on the IoT devices can cause a problem on the overall operation of the IoT system. Traditional ways in the management of IoT devices is a maintenance officer require to check each device every day [1, 3]. Any faulty devices found needs to be fixed or replaced. This traditional method is not practical and very challenging especially in the management of a large scale deployment of IoT consist of hundreds or thousands devices. Because of this, we proposed a faulty sensor detection and identification mechanism using multivariate sensors. Two methods of decision making are introduced in detecting faulty sensors, which are logical and correlation method that implemented in smart parking system and smart agriculture system accordingly. The logical method compares state of all sensors (ultrasound, IR and hall-effect) in the smart parking system either a parking lot is occupied or available, and then determine the condition of the sensors. The drawback of this method is not able to detect faulty sensor properly for a constant fault, which the sensor reading remains the same value. The correlation method calculates the correlation between all sensors (soil moisture, soil temperature and soil water) in the smart agriculture system. This method uses a moving window technique to calculate the correlation for all sensor over time. Any incomparable and uncorrelated sensor readings means a presence of faulty sensors. Based on the experiment results, the findings shows that the proposed faulty sensor detection mechanism is working properly in detecting faulty sensor in a timely manner.

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“…This system of interrelated physical systems and computing devices introduces many opportunities as every object in the system can communicate with related objects of the system by using two-way communications. Specifically talking about energy systems, IoT could offer advanced connectivity of heterogeneous objects to form a single system [2]. However, there are some challenges in seamless integration of different domains once various services have to be offered beyond machine-to-machine (M2M) communications.…”

Section: Introductionmentioning

confidence: 99%

“…The situation gets worse as a number of systems such as power systems, control systems, and communication systems are integrated into a bigger system while each is following its unique set of objectives. Although a great effort can be found in the literature about every issue of energy systems, integration of subsystems is a hot research topic at this time [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Internet of Things for Modern Energy Systems: State-of-the-Art, Challenges, and Open Issues

et al. 2018

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The Internet of Things (IoT) is beginning to shape the future of many industries and emerging markets. One of the target markets for IoT is the energy systems. IoT is a matter of producing, transferring, and processing information, therefore all parts of the system including software and hardware parts should be considered as a whole. In this paper, a state-of-the-art of the IoT-based energy systems is presented to review the recent activities on every component of IoT in energy systems. Challenges in this subject area are discussed, and some solutions are presented thereafter.

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Middleware for Internet of Things: Survey and Challenges

Cited by 20 publications

References 30 publications

Innovation landscape and challenges of smart technologies and systems – a European perspective

Innovation landscape and challenges of smart technologies and systems – a European perspective

Faulty sensor detection using multi-variate sensors in internet of things (IoTs)

Internet of Things for Modern Energy Systems: State-of-the-Art, Challenges, and Open Issues

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