Chp. 6<\/p>\n
Time is an important dimension of GIS Data. You can imagine how time is important to GIS data including showing change throughout a certain time period or just when and where an activity was observed. That\u2019s all time. There’s four keywords to this.\u00a0<\/span><\/p>\n Moving<\/b>: cars, ambulances, airplane feeds<\/span><\/p>\n Discrete<\/b>: criminal incidents. Earthquakes, instagram feeds.\u00a0<\/span><\/p>\n Stationary<\/b>: wind speed, highway and street traffic speed<\/span><\/p>\n Change<\/b>: flooded areas, land use and land cover changes\u00a0<\/span><\/p>\n In spatiotemporal GIS data, the time of an event can be duration or a point in time:<\/span><\/p>\n Point in time<\/b>: The moment a lightning strike occurs<\/span><\/p>\n Duration in time<\/b>: When a wildfire starts and ends.\u00a0<\/span><\/p>\n Key terms:<\/span><\/p>\n Time measurement in other words:<\/b> Time can be expressed in many units such as in years, months, days, etc.\u00a0<\/span><\/p>\n Time reference systems(time zones):<\/b> The most often used time zones are GMT and UTC. Both reference the prime meridian.\u00a0<\/span><\/p>\n Time representations: <\/b>Time can be represented in different formats and languages 12\/18\/2020 or write it out.\u00a0<\/span><\/p>\n Temporal resolution<\/b>: refers to the time interval at which events are sampled.\u00a0<\/span><\/p>\n IoT: The network of physical objects, or things embedded with sensor and network connectivity that enable these objects to collect and exchange data. This can be in airplanes, heart monitors, taxis, and more.\u00a0<\/span><\/p>\n Enterprise IoT applications:<\/b> Include smart cities, infrastructure management, environment quality monitoring, small retail-inventory management, and precise agriculture.\u00a0<\/span><\/p>\n Consumer IoT:<\/b> include connected cars, connected health and smart homes.\u00a0<\/span><\/p>\n ArcGIS Analytics for IoT and GeoEvent Server share similar components.\u00a0<\/span><\/p>\n Ingest: <\/b>This component interacts with various data sources. IT provides ways to communicate with IoT platforms, sensor networks, and more\u00a0<\/span><\/p>\n Process:<\/b> This component processes the real-time data received and translated by the ingestion component.\u00a0<\/span><\/p>\n Outputs:<\/b> The output component sends processed data to a variety of destinations. For example, sending alerts via email or SMS.\u00a0<\/span><\/p>\n Other key definitions<\/span><\/p>\n Feed items: <\/b>Allows users to received sensor inputs<\/span><\/p>\n Real-time analytic items: <\/b>Allows users to perform real-item processing of those inputs including triggering alerts and actions.\u00a0<\/span><\/p>\n Big data analytic items<\/b>: Allow users to access and analyze big data repositories of historical observations.<\/span><\/p>\n Poll:<\/b> the traditional approach in which a client periodically polls the server to retrieve the latest data.\u00a0<\/span><\/p>\n Push<\/b>: a new way to serve data in near real time using the HTML5 WebSocket protocol.\u00a0<\/span><\/p>\n For this, I would make a dashboard app based on the voting precincts in Delaware County. We know that voting is becoming more and more important each election so making a dashboard based on this could be ideal. The app would just be taking the users location and showing them all the precincts in the area and what time they close. It would also point and give them directions to the closest precinct according to their app\u2019s location.\u00a0<\/span><\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" Chp. 6 Time is an important dimension of GIS Data. You can imagine how time is important to GIS data including showing change throughout a certain time period or just when and where an activity was observed. That\u2019s all time. There’s four keywords to this.\u00a0 Moving: cars, ambulances, airplane feeds Discrete: criminal incidents. Earthquakes, instagram feeds.\u00a0 Stationary: wind speed, highway and street traffic speed Change: flooded areas, land use and land cover changes\u00a0 In spatiotemporal GIS data, the time of an event can be duration or a point in time: Point in time: The moment a lightning strike occurs Duration in time: When a wildfire starts and ends.\u00a0 Key terms: Time measurement in other words: Time can be expressed in many units such as in years, months, days, etc.\u00a0 Time reference systems(time zones): The most often used time zones are GMT and UTC. Both reference the prime meridian.\u00a0 Time representations: Time can be represented in different formats and languages 12\/18\/2020 or write it out.\u00a0 Temporal resolution: refers to the time interval at which events are sampled.\u00a0 IoT: The network of physical objects, or things embedded with sensor and network connectivity that enable these objects to collect and exchange data. This can be in airplanes, heart monitors, taxis, and more.\u00a0 Enterprise IoT applications: Include smart cities, infrastructure management, environment quality monitoring, small retail-inventory management, and precise agriculture.\u00a0 Consumer IoT: include connected cars, connected health and smart homes.\u00a0 ArcGIS Analytics for IoT and GeoEvent Server share similar components.\u00a0 Ingest: This component interacts with various data sources. IT provides ways to communicate with IoT platforms, sensor networks, and more\u00a0 Process: This component processes the real-time data received and translated by the ingestion component.\u00a0 Outputs: The output component sends processed data to a variety of destinations. For example, sending alerts via email or SMS.\u00a0 Other key definitions Feed items: Allows users to received sensor inputs Real-time analytic items: Allows users to perform real-item processing of those inputs including triggering alerts and actions.\u00a0 Big data analytic items: Allow users to access and analyze big data repositories of historical observations. Poll: the traditional approach in which a client periodically polls the server to retrieve the latest data.\u00a0 Push: a new way to serve data in near real time using the HTML5 WebSocket protocol.\u00a0 For this, I would make a dashboard app based on the voting precincts in Delaware County. We know that voting is becoming more and more important each election so making a dashboard based on this could be ideal. The app would just be taking the users location and showing them all the precincts in the area and what time they close. It would also point and give them directions to the closest precinct according to their app\u2019s location.\u00a0 <\/p>\n","protected":false},"author":2207,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-663","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/posts\/663","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/users\/2207"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/comments?post=663"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/posts\/663\/revisions"}],"predecessor-version":[{"id":664,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/posts\/663\/revisions\/664"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/media?parent=663"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/categories?post=663"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/tags?post=663"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}