Towards a Generalized Approach for Deep Neural Network Based Event Processing for the Internet of Multimedia Things

Aslam, Asra; Curry, Edward

doi:10.1109/access.2018.2823590

Cited by 40 publications

(24 citation statements)

References 36 publications

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“…We are investigating support services for rich content types including text and multimedia streams within the dataspace that leverage advances in deep learning for image processing (e.g. object detection) [52].…”

Section: Discussionmentioning

confidence: 99%

A Real-time Linked Dataspace for the Internet of Things: Enabling “Pay-As-You-Go” Data Management in Smart Environments

Curry

Derguech

Hasan

et al. 2019

Future Generation Computer Systems

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Section: Discussionmentioning

confidence: 99%

A Real-time Linked Dataspace for the Internet of Things: Enabling “Pay-As-You-Go” Data Management in Smart Environments

Curry

Derguech

Hasan

et al. 2019

Future Generation Computer Systems

Self Cite

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“…Smart cities present a fertile application domain as they need extensive monitoring of multiple scenarios, including traffic monitoring; security checks; and disaster management, all of which generate large amounts of data. The work in Reference [2], to tackle the problem of efficient analysis of multimedia events, presents a combination of event and multimedia processing systems. Users queries are forwarded to a Multimedia Stream Processing Engine (MSPE), where queries are resolved according to what event a user has subscribed to.…”

Section: Overloaded Multimedia Networkmentioning

confidence: 99%

“…For a long time, the IoT infrastructure has been linked to event-based systems. These systems [2] identify events, which cause streaming of structured or scalar data, for example the streaming of the ambient temperature of an object or its energy consumption. On the other hand, camera sensors detect multimedia events and, hence, communicate unstructured data.…”

Section: Introductionmentioning

confidence: 99%

Real-Time, Content-Based Communication Load Reduction in the Internet of Multimedia Things

et al. 2020

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There is an increasing number of devices available for the Internet of Multimedia Things (IoMT). The demands these ever-more complex devices make are also increasing in terms of energy efficiency, reliability, quality-of-service guarantees, higher data transfer rates, and general security. The IoMT itself faces challenges when processing and storing massive amounts of data, transmitting it over low bandwidths, bringing constrained resources to bear and keeping power consumption under check. This paper’s research focuses on an efficient video compression technique to reduce that communication load, potentially generated by diverse camera sensors, and also improve bit-rates, while ensuring accuracy of representation and completeness of video data. The proposed method applies a video content-based solution, which, depending on the motion present between consecutive frames, decides on whether to send only motion information or no frame information at all. The method is efficient in terms of limiting the data transmitted, potentially conserving device energy, and reducing latencies by means of negotiable processing overheads. Data are also encrypted in the interests of confidentiality. Video quality measurements, along with a good number of Quality-of-Service measurements demonstrated the value of the load reduction, as is also apparent from a comparison with other related methods.

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“…Figure 2 shows an illustration of the IoT architecture which could be aided by RFID, optical tags, QR codes, Bluetooth low energy, Wi-Fi direct, and LTE-Advanced, among others. Most of the scholars emphasize improvement of efficiency for handling a lot of realtime information (info) but ignore multimedia transmission aspects [7,8]. e direction of research is shifting from the ordinary IoT to the multimedia-based IoT because of the need to enable smart devices to efficiently observe, sense, and understand their environment through multimedia data [9,10], hence resulting in the emergence of the newer field of Internet of multimedia things (IoMT).…”

Section: E Architecture Of a Wmsnmentioning

confidence: 99%

“…IoT system functionality should therefore be upgraded to the IoMT. We compare the two as discussed in [7]: (v) IoT devices are deployed in application-dependent RFID tags, but the IoMT is in video and audio sensors. (vi) In terms of service composition, the IoMT has no available specialized middleware, whereas the IoT has specialized service-oriented, architecture-based, and event-based middleware.…”

Section: E Internet Of Ingsmentioning

confidence: 99%

QoS Strategies for Wireless Multimedia Sensor Networks in the Context of IoT at the MAC Layer, Application Layer, and Cross-Layer Algorithms

Bernard

Pei

Kimbugwe

2019

Journal of Computer Networks and Communications

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Wireless multimedia sensor networks (WMSNs) have got capacity to collect both scalar sensor data and multidimensional sensor data. It is the basis for the Internet of things (IoT). Quality of service (QoS) pointers like energy efficiency, reliability, bit error rate, and latency can be helpful in data collection estimation over a network. In this paper, we review a number of QoS strategies for WMSNs and wireless sensor networks (WSNs) in the IoT context from the perspective of the MAC and application layers as well as the cross-layer paradigm. Considering the MAC layer, since it is responsible for regulating the admittance to the shared medium and transmission reliability and efficiency through error correction in wireless transmissions, and for performance of framing, addressing, and flow control, the MAC protocol design greatly affects energy efficiency. We thus review a number of protocols here including contention-free and contention-based protocols as well as the hybrid of these. This paper also surveys a number of state-of-the-art machine-to-machine, publish/subscribe, and request/response protocols at the application layer. Cross-layer QoS strategies are very vital when it comes to system optimization. Many cross-layer strategies have been reviewed. For these QoS strategies, the challenges and opportunities are reviewed at each of the layers considered. Lastly, the future research directions for QoS strategies are discussed for research and application before concluding this paper.

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Towards a Generalized Approach for Deep Neural Network Based Event Processing for the Internet of Multimedia Things

Cited by 40 publications

References 36 publications

A Real-time Linked Dataspace for the Internet of Things: Enabling “Pay-As-You-Go” Data Management in Smart Environments

A Real-time Linked Dataspace for the Internet of Things: Enabling “Pay-As-You-Go” Data Management in Smart Environments

Real-Time, Content-Based Communication Load Reduction in the Internet of Multimedia Things

QoS Strategies for Wireless Multimedia Sensor Networks in the Context of IoT at the MAC Layer, Application Layer, and Cross-Layer Algorithms

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