Personalized weather information for low-literate farmers using multimodal dialog systems

Author(s):  
Muhammad Qasim ◽  
Haris Bin Zia ◽  
Awais Athar ◽  
Tania Habib ◽  
Agha Ali Raza
ICCTP 2010 ◽  
2010 ◽  
Author(s):  
Jianping Gao ◽  
Boming Tang ◽  
Haiying Li ◽  
Min Liu ◽  
Chuandong Gao

ICCTP 2011 ◽  
2011 ◽  
Author(s):  
Chenyang Xian ◽  
Xumei Chen ◽  
Bin Li ◽  
Wenfeng Liu ◽  
Lin Wang

2018 ◽  
Author(s):  
Matthew J. Bolton ◽  
William G. Blumberg ◽  
Lara K. Ault ◽  
H. Michael Mogil ◽  
Stacie H. Hanes

Weather is important to all people, including vulnerable populations (those whose circumstances include cognitive processing, hearing, or vision differences, physical disability, homelessness, and other scenarios and factors). Autism spectrum conditions (ASC) affect information-processing and areas of neurological functioning that potentially inhibit the reception of hazardous weather information, and is of particular concern for weather messengers. People on the autism spectrum tend to score highly in tests of systemizing, a psychological process that heavily entails attention to detail and revolves around the creation of logical rules to explain things that occur in the world. This article reports the results of three preliminary studies examining weather salience–psychological attention to weather–and its potential relationships with systemizing in autistic people. Initial findings suggest that enhanced weather salience exists among autistic individuals compared to those without the condition, and that this may be related to systemizing. These findings reveal some possible strategies for communicating weather to autistic populations and motivate future work on a conceptual model that blends systemizing and chaos theory to better understand weather salience.


Author(s):  
Ronnie W. Smith ◽  
D. Richard Hipp

As spoken natural language dialog systems technology continues to make great strides, numerous issues regarding dialog processing still need to be resolved. This book presents an exciting new dialog processing architecture that allows for a number of behaviors required for effective human-machine interactions, including: problem-solving to help the user carry out a task, coherent subdialog movement during the problem-solving process, user model usage, expectation usage for contextual interpretation and error correction, and variable initiative behavior for interacting with users of differing expertise. The book also details how different dialog problems in processing can be handled simultaneously, and provides instructions and in-depth result from pertinent experiments. Researchers and professionals in natural language systems will find this important new book an invaluable addition to their libraries.


2016 ◽  
Vol 16 (3) ◽  
pp. 643-661 ◽  
Author(s):  
Kostas Kalabokidis ◽  
Alan Ager ◽  
Mark Finney ◽  
Nikos Athanasis ◽  
Palaiologos Palaiologou ◽  
...  

Abstract. We describe a Web-GIS wildfire prevention and management platform (AEGIS) developed as an integrated and easy-to-use decision support tool to manage wildland fire hazards in Greece (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing online access to information that is essential for wildfire management. The system uses a number of spatial and non-spatial data sources to support key system functionalities. Land use/land cover maps were produced by combining field inventory data with high-resolution multispectral satellite images (RapidEye). These data support wildfire simulation tools that allow the users to examine potential fire behavior and hazard with the Minimum Travel Time fire spread algorithm. End-users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations, i.e., single-fire propagation, point-scale calculation of potential fire behavior, and burn probability analysis, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANNs) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps are used to generate integrated output map of fire hazard prediction. The system also incorporates weather information obtained from remote automatic weather stations and weather forecast maps. The system and associated computation algorithms leverage parallel processing techniques (i.e., High Performance Computing and Cloud Computing) that ensure computational power required for real-time application. All AEGIS functionalities are accessible to authorized end-users through a web-based graphical user interface. An innovative smartphone application, AEGIS App, also provides mobile access to the web-based version of the system.


2021 ◽  
Vol 35 (1) ◽  
pp. 64-76
Author(s):  
Sarah Opitz-Stapleton ◽  
Roger Street ◽  
Qian Ye ◽  
Jiarui Han ◽  
Chris D. Hewitt

AbstractThe Climate Science for Service Partnership China (CSSP China) is a joint program between China and the United Kingdom to build the basis for climate services to support the weather and climate resilient economic development and welfare in China. Work Package 5 (WP5) provides the translational science on identification of: different users and providers, and their mandates; factors contributing to communication gaps and capacities between various users and providers; and mechanisms to work through such issues to develop and/or evolve a range of climate services. Key findings to emerge include that users from different sectors have varying capacities, requirements, and needs for information in their decision contexts, with a current strong preference for weather information. Separating climate and weather services when engaging users is often not constructive. Furthermore, there is a need to move to a service delivery model that is more user-driven and science informed; having sound climate science is not enough to develop services that are credible, salient, reliable, or timely for diverse user groups. Greater investment in building the capacity of the research community supporting and providing climate services to conduct translational sciences and develop regular user engagement processes is much needed. Such a move would help support the China Meteorological Administration’s (CMA) ongoing efforts to improve climate services. It would also assist in potentially linking a broader group of “super” users who currently act as providers and purveyors of climate services because they find the existing offerings are not relevant to their needs or cannot access CMA’s services.


Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 341
Author(s):  
Carolina Rodriguez-Paras ◽  
Johnathan T. McKenzie ◽  
Pasakorn Choterungruengkorn ◽  
Thomas K. Ferris

Despite the increasing availability of technologies that provide access to aviation weather information in the cockpit, weather remains a prominent contributor to general aviation (GA) accidents. Pilots fail to detect the presence of new weather information, misinterpret it, or otherwise fail to act appropriately on it. When cognitive demands imposed by concurrent flight tasks are high, the risks increase for each of these failure modes. Previous research shows how introducing vibrotactile cues can help ease or redistribute some of these demands, but there is untapped potential in exploring how vibratory cues can facilitate “interruption management”, i.e., fitting the processing of available weather information into flight task workflow. In the current study, GA pilots flew a mountainous terrain scenario in a flight training device while receiving, processing, and acting on various weather information messages that were displayed visually, in graphical and text formats, on an experimental weather display. Half of the participants additionally received vibrotactile cues via a connected smartwatch with patterns that conveyed the “severity” of the message, allowing pilots to make informed decisions about when to fully attend to and process the message. Results indicate that weather messages were acknowledged more often and faster when accompanied by the vibrotactile cues, but the time after acknowledgment to fully process the messages was not significantly affected by vibrotactile cuing, nor was overall situation awareness. These findings illustrate that severity-encoded vibrotactile cues can support pilot awareness of updated weather as well as task management in processing weather messages while managing concurrent flight demands.


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