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<html xmlns="http://www.w3.org/1999/xhtml"> <head> <meta charset="utf-8"> <meta name="generator" content="pdf2htmlEX"> <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"> <link rel="stylesheet" href="https://static.pudn.com/base/css/base.min.css"> <link rel="stylesheet" href="https://static.pudn.com/base/css/fancy.min.css"> <link rel="stylesheet" href="https://static.pudn.com/prod/directory_preview_static/62594d2abe9ad24cfab50b50/raw.css"> <script src="https://static.pudn.com/base/js/compatibility.min.js"></script> <script src="https://static.pudn.com/base/js/pdf2htmlEX.min.js"></script> <script> try{ pdf2htmlEX.defaultViewer = new pdf2htmlEX.Viewer({}); }catch(e){} </script> <title></title> </head> <body> <div id="sidebar" style="display: none"> <div id="outline"> </div> </div> <div id="pf1" class="pf w0 h0" data-page-no="1"><div class="pc pc1 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/62594d2abe9ad24cfab50b50/bg1.jpg"><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">J Supercomput</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">DOI 10.1007/s11227-016-1769-9</div><div class="t m0 x1 h3 y3 ff2 fs1 fc0 sc0 ls1 ws0">Real-time wireless multisensory smart surveillance with</div><div class="t m0 x1 h3 y4 ff2 fs1 fc0 sc0 ls1 ws0">3D-HEVC streams for internet-of-things (IoT)</div><div class="t m0 x1 h4 y5 ff2 fs2 fc0 sc0 ls2 ws0">George Kokkonis</div><div class="t m0 x2 h5 y6 ff2 fs3 fc0 sc0 ls1 ws0">1</div><div class="t m0 x3 h4 y5 ff3 fs2 fc0 sc0 ls1 ws0">· Kostas E. Psannis</div><div class="t m0 x4 h5 y6 ff2 fs3 fc0 sc0 ls1 ws0">1</div><div class="t m0 x5 h6 y5 ff3 fs2 fc0 sc0 ls1 ws0">·</div><div class="t m0 x1 h4 y7 ff2 fs2 fc0 sc0 ls4 ws0">Manos Roumeliotis</div><div class="t m0 x3 h5 y8 ff2 fs3 fc0 sc0 ls1 ws0">1</div><div class="t m0 x6 h4 y9 ff3 fs2 fc0 sc0 ls1 ws0">· Dan Schonfeld</div><div class="t m0 x7 h5 y8 ff2 fs3 fc0 sc0 ls1 ws0">2</div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls5 ws0">© Springer Science+Business Media New York 2016</div><div class="t m0 x1 h4 yb ff2 fs2 fc0 sc0 ls4 ws0">Abstract This paper presents the design of a novel, real-time, wireless, multisen-</div><div class="t m0 x1 h7 yc ff1 fs2 fc0 sc0 ls3 ws0">sory, smart surveillance system with 3D-HEVC features. The proposed high-level</div><div class="t m0 x1 h7 yd ff1 fs2 fc0 sc0 ls4 ws0">system architecture of the surveillance system is analyzed. The advantages of HEVC</div><div class="t m0 x1 h7 ye ff1 fs2 fc0 sc0 ls4 ws0">encoding are presented. Methods for synchronization between multiple streams are</div><div class="t m0 x1 h7 yf ff1 fs2 fc0 sc0 ls4 ws0">presented. Available wireless standards are presented and compared. A network-</div><div class="t m0 x1 h7 y10 ff1 fs2 fc0 sc0 ls3 ws0">adaptive transmission protocol for a reliable, real-time, multisensory surveillance</div><div class="t m0 x1 h7 y11 ff1 fs2 fc0 sc0 ls4 ws0">system is proposed. Adaptive packet frame grouping (APFG) and adaptive quanti-</div><div class="t m0 x1 h7 y12 ff1 fs2 fc0 sc0 ls3 ws0">zation are deployed to maximize the quality-of-experience (QoE). Measurements of</div><div class="t m0 x1 h7 y13 ff1 fs2 fc0 sc0 ls3 ws0">the proposed protocol have been shown to provide superior results compared to exist-</div><div class="t m0 x1 h7 y14 ff1 fs2 fc0 sc0 ls3 ws0">ing transport protocols.</div><div class="t m0 x1 h4 y15 ff2 fs2 fc0 sc0 ls6 ws0">Keywords Smart surveillance · Internet-of-things (IoT) · HEVC · Depth cameras ·</div><div class="t m0 x1 h7 y16 ff1 fs2 fc0 sc0 ls3 ws0">Real-time transport protocols · Wireless transmission</div><div class="t m0 x1 h8 y17 ff5 fs4 fc0 sc0 ls1 ws0">B</div><div class="t m0 x8 h2 y18 ff1 fs0 fc0 sc0 ls0 ws0">George Kokkonis</div><div class="t m0 x8 h2 y19 ff1 fs0 fc0 sc0 ls0 ws0">gkokkonis@uom.gr</div><div class="t m0 x8 h2 y1a ff1 fs0 fc0 sc0 ls8 ws0">Kostas E. Psannis</div><div class="t m0 x8 h2 y1b ff1 fs0 fc0 sc0 ls1 ws0">kpsannis@uom.gr</div><div class="t m0 x8 h2 y1c ff1 fs0 fc0 sc0 ls1 ws0">Manos Roumeliotis</div><div class="t m0 x8 h2 y1d ff1 fs0 fc0 sc0 ls1 ws0">manos@uom.gr</div><div class="t m0 x8 h2 y1e ff1 fs0 fc0 sc0 ls5 ws0">Dan Schonfeld</div><div class="t m0 x8 h2 y1f ff1 fs0 fc0 sc0 ls1 ws0">dans@uic.edu</div><div class="t m0 x1 h9 y20 ff1 fs5 fc0 sc0 ls1 ws0">1</div><div class="t m0 x8 h2 y21 ff1 fs0 fc0 sc0 ls5 ws0">Department of Applied Informatics, University of Macedonia, 156 Egnatia Street,</div><div class="t m0 x8 h2 y22 ff1 fs0 fc0 sc0 ls1 ws0">54006 Thessaloniki, Greece</div><div class="t m0 x1 h9 y23 ff1 fs5 fc0 sc0 ls1 ws0">2</div><div class="t m0 x8 h2 y24 ff1 fs0 fc0 sc0 ls1 ws0">Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago,</div><div class="t m0 x8 h2 y25 ff1 fs0 fc0 sc0 ls0 ws0">IL 60607-7053, USA</div><div class="t m0 x9 ha y26 ff6 fs6 fc0 sc0 ls1 ws0">123</div><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a></div><div class="pi" data-data='{"ctm":[2.037103,0.000000,0.000000,2.037103,0.000000,0.000000]}'></div></div> </body> </html>

<div id="pf2" class="pf w0 h0" data-page-no="2"><div class="pc pc2 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/62594d2abe9ad24cfab50b50/bg2.jpg"><div class="t m0 xa h2 y1 ff1 fs0 fc0 sc0 ls5 ws0">G. Kokkonis et al.</div><div class="t m0 x1 hb y27 ff2 fs7 fc0 sc0 ls1 ws0">1 Introduction</div><div class="t m0 x1 h7 y28 ff1 fs2 fc0 sc0 ls4 ws0">The internet has revolutionized the computer applications and communications. From</div><div class="t m0 x1 h7 y29 ff1 fs2 fc0 sc0 ls4 ws0">the s imple transfer of text messages we have moved to the Web 2, the machine-to-</div><div class="t m0 x1 h7 y2a ff1 fs2 fc0 sc0 ls4 ws0">machine (M2M) communications and the transfer of real-time audio, video, and other</div><div class="t m0 x1 h7 y2b ff1 fs2 fc0 sc0 ls4 ws0">multisensory data, all together called supermedia. The new evolution stage of the inter-</div><div class="t m0 x1 h7 y2c ff1 fs2 fc0 sc0 ls3 ws0">net is the internet-of-things (IoT). Internet of things semantically means a worldwide</div><div class="t m0 x1 h7 y2d ff1 fs2 fc0 sc0 ls4 ws0">network of interconnected object uniquely addressable, based on standard com-</div><div class="t m0 x1 h7 y2e ff1 fs2 fc0 sc0 ls4 ws0">munication protocols [1]. Person-to-person, person-to-object, and object-to-object</div><div class="t m0 x1 h7 y2f ff1 fs2 fc0 sc0 ls3 ws0">communication is now thriving. Humans, sensors, actuators, and smart objects are</div><div class="t m0 x1 h7 y30 ff1 fs2 fc0 sc0 ls3 ws0">exchanging vast, real-time information.</div><div class="t m0 xb h7 y31 ff1 fs2 fc0 sc0 ls4 ws0">One main sector of the IoT is the efﬁcient encoding and transferring of video streams</div><div class="t m0 x1 h7 y32 ff1 fs2 fc0 sc0 ls4 ws0">over the internet. The new high-efﬁciency video encoding (HEVC) offers more than</div><div class="t m0 x1 h7 y33 ff1 fs2 fc0 sc0 ls4 ws0">50 % improvement in video compression over its predecessor H.264 advanced video</div><div class="t m0 x1 h7 y34 ff1 fs2 fc0 sc0 ls4 ws0">coding standard, with the same image quality, at the expense of the increased com-</div><div class="t m0 x1 h7 y35 ff1 fs2 fc0 sc0 ls4 ws0">putational complexity [2]. The 50 % improvement of video compression corresponds</div><div class="t m0 x1 h7 y36 ff1 fs2 fc0 sc0 ls3 ws0">to 50 % bit rate reduction for video transferring over the IoT. This reduction is cru-</div><div class="t m0 x1 h7 y37 ff1 fs2 fc0 sc0 ls1 ws0">cial, especially in real-time video monitoring for smart surveillance systems. Smart</div><div class="t m0 x1 h7 y38 ff1 fs2 fc0 sc0 ls3 ws0">surveillance is the use of automatic video analysis technologies in video surveil-</div><div class="t m0 x1 h7 y39 ff1 fs2 fc0 sc0 ls3 ws0">lance applications. Smart surveillance systems often deal with real-time monitoring</div><div class="t m0 x1 h7 y3a ff1 fs2 fc0 sc0 ls3 ws0">of persistent and transient objects/people within a speciﬁc environment. They use</div><div class="t m0 x1 h7 y3b ff1 fs2 fc0 sc0 ls4 ws0">image processing algorithms for detection, tracking, and understanding of moving</div><div class="t m0 x1 h7 y3c ff1 fs2 fc0 sc0 ls3 ws0">objects/people of interest in dynamic scenes. The main stages of processing in an</div><div class="t m0 x1 h7 y3d ff1 fs2 fc0 sc0 ls3 ws0">intelligent visual surveillance system are as follows: moving object detection and</div><div class="t m0 x1 h7 y3e ff1 fs2 fc0 sc0 ls4 ws0">recognition, tracking, behavioural analysis, and retrieval [3].</div><div class="t m0 xb h7 y3f ff1 fs2 fc0 sc0 ls3 ws0">The smart surveillance systems are divided in two main categories, depending on</div><div class="t m0 x1 h7 y40 ff1 fs2 fc0 sc0 ls4 ws0">where the video analysis is made. The ﬁrst category includes cameras with process-</div><div class="t m0 x1 h7 y41 ff1 fs2 fc0 sc0 ls4 ws0">ing capabilities. The detection of the event and the storage of the event are made</div><div class="t m0 x1 h7 y42 ff1 fs2 fc0 sc0 ls4 ws0">autonomously by the camera. Such cameras are called smart cameras [4]. In the sec-</div><div class="t m0 x1 h7 y43 ff1 fs2 fc0 sc0 ls3 ws0">ond category, the video stream is transferred through the network in datacenters where</div><div class="t m0 x1 h7 y44 ff1 fs2 fc0 sc0 ls3 ws0">the video analysis is made. Large research projects on this category are the visual</div><div class="t m0 x1 h7 y45 ff1 fs2 fc0 sc0 ls3 ws0">surveillance and monitoring (VSAM) [5], the annotated digital video for intelligent</div><div class="t m0 x1 h7 y46 ff1 fs2 fc0 sc0 ls3 ws0">surveillance and optimized retrieval (ADVISOR) [6], and the smart surveillance sys-</div><div class="t m0 x1 h7 y47 ff1 fs2 fc0 sc0 ls4 ws0">tem of IBM [7]. In the third-generation surveillance systems (3GSS) [8] a mixture of</div><div class="t m0 x1 h7 y48 ff1 fs2 fc0 sc0 ls4 ws0">these categories is made; both smart cameras and large datacenters are being used. The</div><div class="t m0 x1 h7 y49 ff1 fs2 fc0 sc0 ls4 ws0">video analysis often includes image enhancement [9], motion detection [10], object</div><div class="t m0 x1 h7 y4a ff1 fs2 fc0 sc0 ls4 ws0">tracking [11], and behavior understanding [12].</div><div class="t m0 xb h7 y4b ff1 fs2 fc0 sc0 ls4 ws0">Smart surveillance systems can be enhanced with the help of 3D monitoring tech-</div><div class="t m0 x1 h7 y4c ff1 fs2 fc0 sc0 ls4 ws0">nologies. The 3D camera, also called time-of-ﬂight or depth camera, emits modulated</div><div class="t m0 x1 h7 y4d ff1 fs2 fc0 sc0 ls3 ws0">infrared light and measures the time the infrared signal takes to travel from the camera</div><div class="t m0 x1 h7 y4e ff1 fs2 fc0 sc0 ls4 ws0">to the object and back again: the elapsed time is called “time of ﬂight”.</div><div class="t m0 xb h7 y4f ff1 fs2 fc0 sc0 ls3 ws0">As we are heading towards the 5th generation of wireless/mobile broadband net-</div><div class="t m0 x1 h7 y50 ff1 fs2 fc0 sc0 ls4 ws0">works, numerous devices and networks are interconnected. The internet of things</div><div class="t m0 x1 h7 y51 ff1 fs2 fc0 sc0 ls3 ws0">(IOT) is becoming a reality. Person-to-person, person-to-object, and object-to-object</div><div class="t m0 x1 h7 y52 ff1 fs2 fc0 sc0 ls3 ws0">are exchanging continuously massive real-time supermedia data. The efﬁcient trans-</div><div class="t m0 x1 h7 y53 ff1 fs2 fc0 sc0 ls3 ws0">mission of this data is of great importance for t he smart surveillance systems. The</div><div class="t m0 x1 ha y54 ff6 fs6 fc0 sc0 ls1 ws0">123</div><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a></div><div class="pi" data-data='{"ctm":[2.037103,0.000000,0.000000,2.037103,0.000000,0.000000]}'></div></div>

<div id="pf3" class="pf w0 h0" data-page-no="3"><div class="pc pc3 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/62594d2abe9ad24cfab50b50/bg3.jpg"><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls5 ws0">Real-time wireless multisensory smart surveillance...</div><div class="t m0 x1 h7 y27 ff1 fs2 fc0 sc0 ls4 ws0">scope of this paper is to propose a transport protocol for efﬁcient delivery of super-</div><div class="t m0 x1 h7 y55 ff1 fs2 fc0 sc0 ls3 ws0">media data from smart surveillance systems. Flow/congestion control algorithms and</div><div class="t m0 x1 h7 y56 ff1 fs2 fc0 sc0 ls4 ws0">synchronization techniques should be enforced to maximize efﬁciency of a smart</div><div class="t m0 x1 h7 y57 ff1 fs2 fc0 sc0 ls1 ws0">surveillance system.</div><div class="t m0 xb h7 y58 ff1 fs2 fc0 sc0 ls4 ws0">The rest of the paper is organized as follows: Sect. 2 presents a high-level system</div><div class="t m0 x1 h7 y59 ff1 fs2 fc0 sc0 ls3 ws0">architecture for smart surveillance systems. Section 3 outlines the characteristics of an</div><div class="t m0 x1 h7 y5a ff1 fs2 fc0 sc0 ls4 ws0">HEVC-3D depth video monitoring. Section 4 proposes a synchronization algorithm</div><div class="t m0 x1 h7 y5b ff1 fs2 fc0 sc0 ls4 ws0">for intra and inter media synchronization between RGB video, Depth video, audio,</div><div class="t m0 x1 h7 y5c ff1 fs2 fc0 sc0 ls4 ws0">and other multisensory data. Section 5 presents the wireless network infrastructure</div><div class="t m0 x1 h7 y5d ff1 fs2 fc0 sc0 ls3 ws0">of the surveillance system. Section 6 analyzes the proposed protocol for t ransferring</div><div class="t m0 x1 h7 y5e ff1 fs2 fc0 sc0 ls3 ws0">multisensory data streams through the wireless IoT networks. Section 7 presents a</div><div class="t m0 x1 h7 y5f ff1 fs2 fc0 sc0 ls1 ws0">case study for transferring a wireless multisensory 3D-HEVC stream over wireless</div><div class="t m0 x1 h7 y60 ff1 fs2 fc0 sc0 ls3 ws0">networks. Finally Sect. 8 concludes this paper.</div><div class="t m0 x1 hb y61 ff2 fs7 fc0 sc0 lsb ws0">2 Smart surveillance systems</div><div class="t m0 x1 h7 y62 ff1 fs2 fc0 sc0 ls3 ws0">As the number of threats of burglary, robbery, and terrorist activities increase, sur-</div><div class="t m0 x1 h7 y63 ff1 fs2 fc0 sc0 ls3 ws0">veillance systems becomes a necessity. The traditional methods for monitoring with</div><div class="t m0 x1 h7 y64 ff1 fs2 fc0 sc0 ls3 ws0">the use of CCTV cameras are now evolving to smart surveillance systems. Threat</div><div class="t m0 x1 h7 y65 ff1 fs2 fc0 sc0 ls3 ws0">detection and video analysis are automatically made by information systems. Instant</div><div class="t m0 x1 h7 y66 ff1 fs2 fc0 sc0 ls3 ws0">notiﬁcation and alerts produced by smart surveillance systems reinforce public safety</div><div class="t m0 x1 h7 y67 ff1 fs2 fc0 sc0 ls3 ws0">and security.</div><div class="t m0 xb h7 y68 ff1 fs2 fc0 sc0 ls4 ws0">Smart surveillance data collected by cameras and sensors can also provide valu-</div><div class="t m0 x1 h7 y69 ff1 fs2 fc0 sc0 ls4 ws0">able decision support analysis to organizations. I ntelligent analytics enhance business</div><div class="t m0 x1 h7 y6a ff1 fs2 fc0 sc0 ls4 ws0">intelligence. The automatic video analytics help organizations to seize opportunities</div><div class="t m0 x1 h7 y6b ff1 fs2 fc0 sc0 ls1 ws0">or revise policies.</div><div class="t m0 xb h7 y6c ff1 fs2 fc0 sc0 ls3 ws0">Smart surveillance systems form a very important sector of video monitoring, video</div><div class="t m0 x1 h7 y6d ff1 fs2 fc0 sc0 ls4 ws0">transmission, and video analysis. Automated recognition of individuals and objects,</div><div class="t m0 x1 h7 y6e ff1 fs2 fc0 sc0 ls3 ws0">pre-determined traits and risks lies at the basis of smart surveillance systems. Some</div><div class="t m0 x1 h7 y6f ff1 fs2 fc0 sc0 ls3 ws0">of the innumerable applications of the smart surveillance systems are</div><div class="t m0 xc h7 y70 ff4 fs2 fc0 sc0 ls1 ws0">• Unattended surveillance for security reasons</div><div class="t m0 xc h7 y71 ff4 fs2 fc0 sc0 ls1 ws0">• Automated inspection for quality assurance</div><div class="t m0 xc h7 y72 ff4 fs2 fc0 sc0 ls1 ws0">• Defect detection and dimensional gauging</div><div class="t m0 xc h7 y73 ff4 fs2 fc0 sc0 ls1 ws0">• Non contact measurements</div><div class="t m0 xc h7 y74 ff4 fs2 fc0 sc0 ls1 ws0">• Part sorting and identiﬁcation</div><div class="t m0 xc h7 y75 ff4 fs2 fc0 sc0 ls1 ws0">• Code reading and veriﬁcation</div><div class="t m0 xc h7 y76 ff4 fs2 fc0 sc0 ls1 ws0">• Robot guidance and automated picking</div><div class="t m0 xc h7 y77 ff4 fs2 fc0 sc0 ls1 ws0">• Biometric recognition and access control</div><div class="t m0 xc h7 y78 ff4 fs2 fc0 sc0 ls1 ws0">• Object detection and tracking</div><div class="t m0 xc h7 y79 ff4 fs2 fc0 sc0 ls1 ws0">• Environment mapping</div><div class="t m0 x1 h7 y7a ff1 fs2 fc0 sc0 ls3 ws0">Apart from video, a smart surveillance system can monitor many more sensory data</div><div class="t m0 x1 h7 y7b ff1 fs2 fc0 sc0 ls2 ws0">such as</div><div class="t m0 xc h7 y7c ff4 fs2 fc0 sc0 ls1 ws0">• Audio</div><div class="t m0 xc h7 y7d ff4 fs2 fc0 sc0 ls1 ws0">• Temperature</div><div class="t m0 x9 ha y54 ff6 fs6 fc0 sc0 ls1 ws0">123</div><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a></div><div class="pi" data-data='{"ctm":[2.037103,0.000000,0.000000,2.037103,0.000000,0.000000]}'></div></div>

<div id="pf4" class="pf w0 h0" data-page-no="4"><div class="pc pc4 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/62594d2abe9ad24cfab50b50/bg4.jpg"><div class="t m0 xa h2 y1 ff1 fs0 fc0 sc0 ls5 ws0">G. Kokkonis et al.</div><div class="t m0 x1 hc y7e ff2 fs0 fc0 sc0 ls8 ws0">Fig. 1 High-level system architecture of a multisensory smart surveillance system</div><div class="t m0 xc h7 y7f ff4 fs2 fc0 sc0 ls1 ws0">• Humidity</div><div class="t m0 xc h7 y80 ff4 fs2 fc0 sc0 ls1 ws0">• Acceleration</div><div class="t m0 xc h7 y81 ff4 fs2 fc0 sc0 ls1 ws0">• Luminosity</div><div class="t m0 xc h7 y82 ff4 fs2 fc0 sc0 ls1 ws0">• Pressure</div><div class="t m0 xc h7 y83 ff4 fs2 fc0 sc0 ls1 ws0">• Chemical analysis</div><div class="t m0 xc h7 y84 ff4 fs2 fc0 sc0 ls1 ws0">• “Time of Flight” depth imaging</div><div class="t m0 xc h7 y85 ff4 fs2 fc0 sc0 ls1 ws0">• Radiation</div><div class="t m0 xc h7 y86 ff4 fs2 fc0 sc0 ls1 ws0">• Ultrasonic waves</div><div class="t m0 xc h7 y87 ff4 fs2 fc0 sc0 ls1 ws0">• Motion</div><div class="t m0 xb h7 y88 ff1 fs2 fc0 sc0 ls4 ws0">All these sensory information is being recording by sensors which are connected to</div><div class="t m0 x1 h7 y89 ff1 fs2 fc0 sc0 ls4 ws0">the surveillance system via the net. The internet of Things is the network which enables</div><div class="t m0 x1 h7 y8a ff1 fs2 fc0 sc0 ls3 ws0">these sensors to collect and exchange data through the existing network infrastructure.</div><div class="t m0 x1 h7 y8b ff1 fs2 fc0 sc0 ls3 ws0">It allows sensors to be identiﬁed and controlled remotely. The IoT improves efﬁciency,</div><div class="t m0 x1 h7 y8c ff1 fs2 fc0 sc0 ls4 ws0">effectiveness. The transport protocols that have already been proposed for the IoT are</div><div class="t m0 x1 h7 y8d ff1 fs2 fc0 sc0 ls4 ws0">the MQTT, the XMPP, the COAP, and the 6LOWPAN [13]. Energy consumption,</div><div class="t m0 x1 h7 y8e ff1 fs2 fc0 sc0 ls3 ws0">safety, and scalability are the main concerns of these protocols.</div><div class="t m0 xb h7 y8f ff1 fs2 fc0 sc0 ls3 ws0">A proposed high-level system architecture of a multisensory smart Surveillance</div><div class="t m0 x1 h7 y90 ff1 fs2 fc0 sc0 ls3 ws0">system is depicted in Fig. 1.</div><div class="t m0 xb h7 y91 ff1 fs2 fc0 sc0 ls3 ws0">In the proposed system architecture three are the main channels that are transferring</div><div class="t m0 x1 h7 y92 ff1 fs2 fc0 sc0 ls4 ws0">information between the monitored environment and the data center.</div><div class="t m0 xb h7 y93 ff1 fs2 fc0 sc0 ls4 ws0">The ﬁrst channel is the video channel. It transfers visual information from the</div><div class="t m0 x1 h7 y94 ff1 fs2 fc0 sc0 ls4 ws0">monitored environment to the data center. In order to lower the bandwidth needed</div><div class="t m0 x1 h7 y95 ff1 fs2 fc0 sc0 ls3 ws0">for this transmission an HEVC encoder is used to lower the bitrate, while keeping the</div><div class="t m0 x1 h7 y96 ff1 fs2 fc0 sc0 ls4 ws0">image quality as good as possible. Network-adaptive congestion control algorithms can</div><div class="t m0 x1 h7 y97 ff1 fs2 fc0 sc0 ls3 ws0">be used to absorb all the available bandwidth without forcing the network to congestion</div><div class="t m0 x1 h7 y98 ff1 fs2 fc0 sc0 ls1 ws0">[14]. The real-time transport protocol (RTP) is often used to transfer information in</div><div class="t m0 x1 h7 y99 ff1 fs2 fc0 sc0 ls1 ws0">this transmission.</div><div class="t m0 x1 ha y54 ff6 fs6 fc0 sc0 ls1 ws0">123</div><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a></div><div class="pi" data-data='{"ctm":[2.037103,0.000000,0.000000,2.037103,0.000000,0.000000]}'></div></div>