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For instance, an image-based search application will require input from a camera on the terminal; the location based application may require GPS information from the GPS module running on the terminal; the schedule planner would require calendar data (meetings, task) from the terminal. (...) This application makes use of GPS information, from the GPS module running in its host, to find the exact current user location. (...) High-level figure Applications describing the use Cloud service customers case Image based Schedule planner search application (Application B) (Application A) - 02/04/2013, e-meeting, 2:00 - 4:00 p.m VD infrastructure Cloud service provider - 02/02/2013, presentation, 1:00 - 2:00 p.m 39°00' 59.11" S, - 02/07/2013 ~ 02/31/2013 94°21' 29.12" W winter vacation 37°00' 26.31" S, 95°28' 39.12" W Cloud service customers 17°00' 16.22" S, 5°20' 11.12" W - 02/10/2013 my birthday 15°02' 26.43" S, 3°12' 34.22" W Cloud service customers GPS information Image from camera Calendar data Y.3503(14)_FIII.4 Derived – Support of DaaS client peripherals requirements Table III.5 – Service continuation for DaaS Legend Use case Use case title Service continuation for DaaS Use case In this scenario, a consumer is using a particular DaaS.
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Score: 1572323.2 - https://www.itu.int/en/publica.../files/basic-html/page573.html
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 Page 1051 - Shaping smarter and more sustainable cities - Striving for sustainable development goals           Basic HTML Version Table of Contents View Full Version Page 1051 - Shaping smarter and more sustainable cities - Striving for sustainable development goals P. 1051 Work FG‐SSC SDO Document Corresponding Standardization Future needs area deliverable(s) working number document title gap in this area and sugges‐ related to this on this released by tions to SG5 work area area this SDO IETF RFC Problem Statement and Re‐ 6606 quirements for IPv6 over Low‐ Power Wireless Personal Area Network (6LoWPAN) Routing IETF RFC Neighbor Discovery Optimiza‐ 6775 tion for IPv6 over Low‐Power Wireless Personal Area Net‐ works (6LoWPANs) IETF 6LoWPAN Bootstrapping and RFC4861 6LoWPAN IPv6 ND Optimiza‐ tions 3.3.3.6 Global position system There is a Technical Report on ICT infrastructure for SSC which involves facilities of IoT in FG‐SSC [b‐FG‐SSC infrastructure]. It is suggested to develop a guideline for application on navigation using GPS in SSC. Work FG‐SSC SDO Document Corresponding Standardization Future needs area deliverable(s) working number document title gap in this area and suggestions related to this on this released by to SG5 work area area this SDO GPS ISO/TC 213 Including 4 kinds: GPS system, To develop (Dimen‐ finite difference GPS, GPS guidelines for sional and enhancement, GPS compati‐ various applica‐ geomet‐ bility and interoperability. tion on location rical prod‐ and navigation uct specifi‐ using GPS in SSC cations and verifi‐ cation) 3.3.3.7 Video surveillance There are Technical Reports on ICT infrastructure for SSC which involves facilities of IoT in FG‐SSC [b‐FG‐SSC infrastructure], and integrated management for SSC [ITU‐T TR management].
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Score: 1478407 - https://www.itu.int/en/publica...files/basic-html/page1051.html
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RESULTS AND DISCUSSION The proposed approach SBQA-SP and its variant SBQA- GP along with existing QBQA algorithms were implemented and tested in typical internet environment. (...) The SSIM index 3depicts the PSNR values corresponding to the SBQA-SP, SBQA-GP and QBQA algorithms. The SBQA-SP 6.3. Multi Scale Structural Similarity (MS-SSIM) algorithm exhibits a higher average PSNR, which is 8% and Measurement 5% higher than the SBQA-GP and QBQA algorithm respectively. (...) QBQA algorithm and 2.2% SBQA-GP algorithm. Figure 5 shows the variation of MS-SSIM values on different consecutive frames.
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Score: 1467519 - https://www.itu.int/en/publica.../files/basic-html/page146.html
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“Emerge ectronic devi f smoke and lving a batter ocedures, inc the cells and tion GP) THE WHO 014 to the Tech Doc 9284) for PONSE TRA 4 of the Tech in responding e. rt 1;4 as prese s the training ency Procedu ices (PEDs) d fire inciden ry fire in a p cluding coolin d re-ignition. DG 3/1 OLE hnical Instruc r incorporati AINING hnical g to a ented g required bo ures” is a req containing li nts involving personal elec ng the device This procedu GP-WG/14-W 10/14 ctions ion in th for quired thium these tronic e with ure is WP/25 DGP-WG/14-WP/25 - 2 - 2. (...) The subject matter to which their various categories of staff should be familiar with is indicated in Table 1-6. . . . — END —
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Score: 1459770.3 - https://www.icao.int/safety/Da...%2014/DGPWG.14.WP.025.2.en.pdf
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Some of the sensors contain GPS modules. These sensors are regarded as the reference points, or marks. The position of other sensors could not be determined without the help of these GPS references. By calculating the distance using the power attenuation from the reference points to the sensors, the positions of these sensors could be determined by hybrid positioning techniques, i.e., GPS and received signal strength indication. (...) Nodes which do not have a GPS module use both the signal received from the GPS node and the distance calculated according to signal attrition to calculate F.747.5(14)_FIII.1 its own location.
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Score: 1453523.4 - https://www.itu.int/wftp3/Publ...files/basic-html/page1006.html
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Revision of Table X.1 - 16 - SCINTEX SCIN tintillation and T EC EX change Format Version 0.31 Table of contents I. (...) APPENDIX: SCINTEX FORMAT DEFINITIONS AND EXAMPLES +----------------------------------------------------------------------------+ | TABLE A1 | | GNSS OBSERVATION DATA FILE - HEADER SECTION DESCRIPTION | +--------------------+------------------------------------------+------------+ | HEADER LABEL | DESCRIPTION | FORMAT | | (Columns61-80) | | | +--------------------+------------------------------------------+------------+ |SCINT VERSION / TYPE| - Format version : 0.31 | F9.2,11X, | | | - File type: SCINTILLATION/TEC DATA | A23,1X | | | - Satellite System: G: GPS | A1,1X, | | | R: GLONASS | A14 | | | E: Galileo | | | | S: SBAS payload | | | | C: BeiDou | | | | J: QZSS | | | | I: IRNSS | | | | M: Mixed | | | | The Description of the Satellite System | | | | is optional, only the A1 is mandatory | | +--------------------+------------------------------------------+------------+ |PGM/ RUN BY /DATE | - Name of program creating current file | A20, | | | - Name of agency creating current file | A20, | | | - Date and time of file creation | | | | Format: yyyymmdd hhmmss zone | A20 | | | zone: 3-4 char. Code for time zone. | | | | UTC recommended | | | | examples: | | | | CET Central European Time | | | | IST Indian Standard Time | | | | JST Japan Standard Time | | | | PDT Pacific Daylight Time | | | | ‘blank’ if not known | | +--------------------+------------------------------------------+------------+ |COMMENT | Comment line(s) | A60 |* +--------------------+------------------------------------------+------------+ |MARKER NAME | Name of antenna marker | A60 | +--------------------+------------------------------------------+------------+ |OBSERVER/AGENCY | Name of the observer / agency | A20,A40 | +--------------------+------------------------------------------+------------+ |REC # / TYPE / VERS | Receiver number, type, and version | 3A20 | +--------------------+------------------------------------------+------------+ |ANT # / TYPE / VERS | Antenna number, type, and version | 3A20 | +--------------------+------------------------------------------+------------+ |APPROX POSITION XYZ | Geocentric approximate marker position | 3F14.4 | | | (Units: Meters, System: ITRS recommended)| | +--------------------+------------------------------------------+------------+ |POSITION LON LAT ALT| Ellipsoidal approximate marker position | 2F14.8, | | | (Units, degrees and meters, System: | F14.4 | | | WGS84 recommended) | | +--------------------+------------------------------------------+------------+ |SYS/ # / OBS TYPES | - Satellite system code (G/R/E/S/C/J/M) | A1 | | | - Number of different observation types | 2X,I3 | | | for the specified satellite system | | | | - Observation descriptors: | 13(1X,A3) | | | +Non-frequency dependent: | | | |o TEC, DEC, AZI, ELE, HTR, WTR, TTR | | | | +Frequency dependent: | | | |o Type | | | |o Band | | | |o Attribute | | | | Use continuation line(s) for more than 13| 6X | | | observation descriptors. | 13(1X,A3) | | | In mixed files: Repeat for each satellite| | | | system. | | | |The following observation descriptors | | | | are defined in SCINTEX Version 0.xx: | | | | Type: | | | |W = S4 | | | |Y = Sigma phase index | | | |S = Raw signal strength | | | |V = S4 correction | | | |T = Lock Time | | | |M = Code Carrier Divergence | | | |N = Sigma Code Carrier Divergence | | | |I = Ionosphere phase delay | | | |J = Satellite Code biases | | | |K = Receiver Code biases | | | | Band: | | | |1= L1 (GPS, QZSS, SBAS) | | | | G1 (GLO) | | | | E2-L1-E1 (GAL) | | | | B1 (BDS) | | | |2= L2 (GPS, QZSS) | | | | G2 (GLO) | | | |5= L5 (GPS, QZSS, SBAS, IRNSS) | | | | E5a (GAL) | | | |6= E6 (GAL) | | | | LEX (QZSS) | | | | B3 (BDS) | | | |7= E5b (GAL) | | | | B2 (BDS) | | | |8= E5a+b (GAL) | | | |9= S (IRNSS) | | | | Attribute: | | | |P = P code-based (GPS,GLO) | | | |C = C code-based (SBAS,GPS,GLO, QZSS) | | | |D = semi-codeless (GPS) | | | |Y = Y code-based (GPS) | | | |M = M code-based (GPS) | | | |N = codeless (GPS) | | | |A = A channel (GAL) | | | |B = B channel (GAL) | | | |C = C channel (GAL) | | | |I = I channel (GPS,GAL, QZSS, BDS) | | | |Q = Q channel (GPS,GAL, QZSS, BDS) | | | |S = M channel (L2C GPS, QZSS) | | | |L = L channel (L2C GPS, QZSS) | | | |S = D channel (GPS, QZSS) | | | |L = P channel (GPS, QZSS) | | | |X = B+C channels (GAL) | | | |X = I+Q channels (GPS,GAL, QZSS, BDS) | | | |X = M+L channels (GPS, QZSS) | | | |X = D+P channels (QZSS) | | | |W = Z-tracking (GPS) | | | |Z = A+B+C channels (GAL) | | | |blank : for types I and X (all) or unknown| | | |tracking mode | | | |All characters in uppercase only!
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Score: 1439208.6 - https://www.itu.int/dms_pub/it...0a/04/R0A0400007C0001MSWE.docx
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 Page 93 - Trends in Telecommunication Reform 2016           Basic HTML Version Table of Contents View Full Version Page 93 - Trends in Telecommunication Reform 2016 P. 93 Figure 3.4: Popular IoT uses INDIVIDUAL COMMUNITY SOCIETY Chapter 3 IoT Smartphones Connected Cars Smart Cities Wearables Health devices Smart Grids Smart homes GPS, Fitbits Intelligent Transport Systems Smart metering Visa PayWave Event Data Recorders (EDRs) Smart water meters Egs. Mastercard Paypass Blood pressure monitors, Traffic monitoring Employee passes remote burglar/heating systems Mobile money Speed, distance, airbag, Electricity/water Data Fitness data, GPS crash locations/alerts, consumption and billing location-based data Heart rate, blood pressure, Traffic flow data Diet, remote heating data Intended Individual person, GP, health authorities, Authorities/regulators Audience Immediate friends/family, health and car insurance, Utility companies Other citizens police, wider friends banks, employers social networks Source: ITU. growth, although cost and reliability remain issues objects to which they are attached, with readers for large-scale systems, as does connectivity. also made easily available. (...) In response, companies are 36 greater innovation in IoT systems. Table 3.2 developing more aesthetically attractive codes that provides an overview of the various challenges can include images, such as the “dot-less visual and opportunities discussed in this section, and codes” being used by Chinese e-commerce giant identifies best practices looking forward.
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Score: 1436978.9 - https://www.itu.int/en/publica...s/files/basic-html/page93.html
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Page 93 - Trends in Telecommunication Reform 2016           Basic HTML Version Table of Contents View Full Version Page 93 - Trends in Telecommunication Reform 2016 P. 93 Figure 3.4: Popular IoT uses INDIVIDUAL COMMUNITY SOCIETY Chapter 3 IoT Smartphones Connected Cars Smart Cities Wearables Health devices Smart Grids Smart homes GPS, Fitbits Intelligent Transport Systems Smart metering Visa PayWave Event Data Recorders (EDRs) Smart water meters Egs. Mastercard Paypass Blood pressure monitors, Traffic monitoring Employee passes remote burglar/heating systems Mobile money Speed, distance, airbag, Electricity/water Data Fitness data, GPS crash locations/alerts, consumption and billing location-based data Heart rate, blood pressure, Traffic flow data Diet, remote heating data Intended Individual person, GP, health authorities, Authorities/regulators Audience Immediate friends/family, health and car insurance, Utility companies Other citizens police, wider friends banks, employers social networks Source: ITU. growth, although cost and reliability remain issues objects to which they are attached, with readers for large-scale systems, as does connectivity. also made easily available. (...) In response, companies are 36 greater innovation in IoT systems. Table 3.2 developing more aesthetically attractive codes that provides an overview of the various challenges can include images, such as the “dot-less visual and opportunities discussed in this section, and codes” being used by Chinese e-commerce giant identifies best practices looking forward.
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Score: 1436978.9 - https://www.itu.int/wftp3/Publ...n/files/basic-html/page93.html
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It is good practice to run these tests on the “data harvest” • Complete and validate the TAL; make sure team every day or every other day. column headers are consistent with data base requirements (see also 11.6). • General yield of data: Check if the number of • Complete and validate the DAL against field test data items from the MSW and the network per- logs; make sure column headers are consistent formance test roughly corresponds to the overall with data base requirements (see also 11.7 for ref- testing time. erence). • Cross-checking with GPS data: If the location per- • Cross-validate DAL and TAL, make sure that team mits, GPS data can be an important source of infor- names are consistent. mation for cross-validation. For instance, the GPS • Cross-validate MSW and ObsTool data, make sure data yield (data points/hour) should correspond that data source ID’s can be resolved to team to the overall testing time. Also, time information names and scenario names. in GPS can provide information for cross-check- ing device settings.
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Score: 1435159.6 - https://www.itu.int/en/publica...s/files/basic-html/page36.html
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In these cases, modern technologies such as Global Positioning Systems (GPS) have the potential to provide more accurate estimates of the crop area. (...) Initially, GPS was used to determine the location of a particular point. (...) In three field-testing countries, the area measured by GPS was used as the gold standard for comparing other measurement methods.
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Score: 1433607 - https://www.fao.org/3/ca6514en/ca6514en.pdf
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