Public Information Systems

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mrbennett2009

Business Education

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Response 1: The process of weather forecasting begins with the collection of as much data as possible about the current state of the atmosphere. Weather data (barometric pressure, humidity, temperature, and wind direction and speed) is collected from a variety of sources, including aircraft, automatic weather stations, weather balloons, buoys, radar, satellites, ships, and trained observers. Due to the variety of data types taken from multiple data sources, weather data is captured in a variety of data formats, primarily Binary Universal Form for the Representation of meteorological data (BUFR) and Institute of Electrical and Electronics Engineers (IEEE) binary. These observations are then converted to a standard format and placed into a gridded 3D model space called the Global Data Assimilation System (GDAS). Once this process is complete, the gridded GDAS output data can be used to start the Global Forecast System (GFS) model. For purposes of this exercise, imagine that the accuracy of the weather forecasts has been slipping. In your role as project manager at the National Center for Environmental Information (NCEI), you have been assigned to lead a project reviewing the processing of the initial data and placing it into the GDAS. Response 2: One business that has benefited through the competitive advantage that was gained through the information systems technology related to an on-demand economy mega trend is Instagram. The Instagram business has done this by becoming a massively powerful big data and data analytics company. Big data and data analytics is when large amounts of data, collected by mobile phones, machine-to-machine sensors, texts, photos, click stream data, internet searches and many other sources, is quickly processed and analyzed. Most big data is unstructured, meaning that the data does not have a predictable format. This type of data is far too complex and in large quantities that traditional technology cannot handle it. Data is collected to gain insight on consumer wants, wishes, or products used to better company's marketing strategies and target customers in a more personal way. Instagram uses big data and data analytics to personalize a user's explore page, target advertising, enhance user experience, fight cyberbullying and offensive comments, and study human conditions. Instagram analyzed 100 million photos, previously an impossible amount of data, to study global clothing patterns. Because of advanced machine learning, machines are capable of extracting enormous amounts of complex data and can transform it into a look into human social, economic, and cultural customs globally. A survey was conducted that exposed Instagram as the social media platform that users experienced the most bullying. Because of this, "they became the first to use machine learning to automatically remove offensive posts, whereas Facebook and Twitter rely on users to report abusive language" (Marr, B., 2018). Marr, B. (2018, Decembe.

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As part of the 2018 HPCC Systems Summit Community Day event: This is a proof-of-concept where an HPCC Systems cluster is used to gather current IoT device data from opt-in subscribers. The cluster's architecture and collected data will be described in the presentation, as well as the additional datasets (e.g. property characteristics, weather, etc.) brought in to enhance the data for analysis using predictive analytics for potential applications in the insurance industry. Dan Camper has been with LexisNexis Risk for four years and is a Senior Architect in the Solutions Lab Group. He has worked for Apple and Dun & Bradstreet, and he ran his own custom programming shop for a decade. He's been writing software professionally for over 35 years and has worked on a myriad of systems, using a lot of different programming languages. He thinks ECL is pretty neat. Hicham Elhassani is VP Modeling with LexisNexis Risk Solutions.

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Weather monitoring and forecasting are very important in agricultural sectors. There are several data need to be collected in real-time to support weather monitoring and forecasting systems, such as temperature, humidity, air pressure, wind speed, wind direction, and rainfall. The purpose of this research to develop a real-time weather monitoring system using a parallel computation approach and analyze the computational performance (i.e., speed up and efficiency) using the ARIMA model. The developed system wireless has been implemented on sensor networks (WSN) platform using Arduino and Raspberry Pi devices and web-based platform for weather visualization and monitoring. The experimental data used in our research work is a set of weather data acquired and collected from January until March 2017 in Bogor area. The result of this research is that the speed up of the using eight processors computation three times faster than using a single processor, with the efficiency of 50%.

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Village agriculture is very important in Bangladesh. In emerging nations like our own, agriculture has a significant impact on national GDP. Basically, because of our current circumstances, the monsoons, which are agriculture's primary source of water, are insufficient. The irrigation system is used in agriculture as a solution to this issue. In this technique, the agricultural field will receive water depending on the type of soil. In agriculture, there are two factors to consider: the soil's moisture content and its fertility. There are already a variety of irrigation options available to lessen the demand for rain. An electrical power on/off schedule controls this kind of method. The use of IOT to create a smart irrigation system is covered in this article. Our method uses hydropumps to regulate multiple pumps at once, which saves time and energy. This system will have a significant impact on the national economy if we implement it.

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The Industrial Internet of Things (IIoT) is one of todays hottest topics within the automation and manufacturing industries. Individuals and organizations that uses variable frequency drives have high expectations that the IIoT ecosystem will deliver on its promises of added value through increased productivity, predictive maintenance, and reduced asset downtime. The idea is to come up with a prototype of a remote monitoring system for VLT FC-302 Danfoss drives. A portal that interfaces with the cloud server and displays the current state of all connected drives.

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