scholarly journals An Unified Representation of Context Knowledge Base for Mobile Context-Aware System

2014 ◽  
Vol 10 (4) ◽  
pp. 581-588 ◽  
Author(s):  
Jang-Seop Jeong ◽  
Dae-Wook Bang
Author(s):  
Darren Black ◽  
Nils Jakob Clemmensen ◽  
Mikael B. Skov

Shopping in the real world is becoming an increasingly interactive experience as stores integrate various technologies to support shoppers. Based on an empirical study of supermarket shoppers, the authors designed a mobile context-aware system called the Context-Aware Shopping Trolley (CAST). The purpose of CAST is to support shopping in supermarkets through context-awareness and acquiring user attention, thus, the authors’ interactive trolley guides and directs shoppers in the handling and finding of groceries. An empirical evaluation showed that shoppers using CAST behaved differently than shoppers using a traditional trolley. Specifically, shoppers using CAST exhibited a more uniform pattern of product collection and found products more easily while travelling a shorter distance. As such, the study finds that CAST supported the supermarket shopping activity.


2010 ◽  
Vol 2 (3) ◽  
pp. 31-43 ◽  
Author(s):  
Darren Black ◽  
Nils Jakob Clemmensen ◽  
Mikael B. Skov

Shopping in the real world is becoming an increasingly interactive experience as stores integrate various technologies to support shoppers. Based on an empirical study of supermarket shoppers, the authors designed a mobile context-aware system called the Context-Aware Shopping Trolley (CAST). The purpose of CAST is to support shopping in supermarkets through context-awareness and acquiring user attention, thus, the authors’ interactive trolley guides and directs shoppers in the handling and finding of groceries. An empirical evaluation showed that shoppers using CAST behaved differently than shoppers using a traditional trolley. Specifically, shoppers using CAST exhibited a more uniform pattern of product collection and found products more easily while travelling a shorter distance. As such, the study finds that CAST supported the supermarket shopping activity.


2016 ◽  
pp. 798-820
Author(s):  
Luca Cagliero

Mobile context-aware systems focus on adapting mobile service provisions to the actual user needs. They offer personalized services based on the context in which mobile users' requests have been submitted. Since contextual information changes over time, the application of established itemset change mining algorithms to context-aware data is an appealing research issue. Change itemset discovery focuses on discovering patterns which represent the temporal evolution of frequent itemsets in consecutive time periods. However, the sparseness of the analyzed data may bias the extraction process, because itemsets are likely to become infrequent at certain time periods. This chapter presents ConChI, a novel context-aware system that performs change itemset mining from context-aware data with the aim at supporting mobile expert decisions. To counteract data sparseness itemset change mining is driven by an analyst-provided taxonomy which allows analyzing data correlation changes at different abstraction levels. In particular, taxonomy is exploited to represent the knowledge that becomes infrequent in certain time periods by means of high level (generalized) itemsets. Experiments performed on real contextual data coming from a mobile application show the effectiveness of the proposed system in supporting mobile user and service profiling.


Author(s):  
Luca Cagliero

Mobile context-aware systems focus on adapting mobile service provisions to the actual user needs. They offer personalized services based on the context in which mobile users’ requests have been submitted. Since contextual information changes over time, the application of established itemset change mining algorithms to context-aware data is an appealing research issue. Change itemset discovery focuses on discovering patterns which represent the temporal evolution of frequent itemsets in consecutive time periods. However, the sparseness of the analyzed data may bias the extraction process, because itemsets are likely to become infrequent at certain time periods. This chapter presents ConChI, a novel context-aware system that performs change itemset mining from context-aware data with the aim at supporting mobile expert decisions. To counteract data sparseness itemset change mining is driven by an analyst-provided taxonomy which allows analyzing data correlation changes at different abstraction levels. In particular, taxonomy is exploited to represent the knowledge that becomes infrequent in certain time periods by means of high level (generalized) itemsets. Experiments performed on real contextual data coming from a mobile application show the effectiveness of the proposed system in supporting mobile user and service profiling.


2015 ◽  
Vol 9 (8) ◽  
pp. 7-14
Author(s):  
Edson D. ◽  
Flávio D.F. ◽  
José O. ◽  
Talles M. ◽  
Adson F.

2018 ◽  
Vol 14 (2) ◽  
pp. 147-164 ◽  
Author(s):  
Sujata Swain ◽  
Rajdeep Niyogi

PurposeThis study aims to discuss a context-aware system, SmartMedicist, which can recommend an alternative medicine from a set of available medicines present at a patient’s home for an unavailable medicine. The system is applied to the chronic disease patients only. The system requires only a smartphone, and provides a reminder to the patient to take medicine at appropriate times and to procure medicines from drug store. The system discusses the output method for the physically challenged patient. Although there are existing systems that can remind a patient for taking medicines, the authors are not aware of any such system that has the capability to recommend an alternative medicine for the prescribed medicine.Design/methodology/approachThe study developed a pharmacology knowledge base that consists of a representation of a set of diseases, according to family, type and medicines, in a k-ary tree. An alternative medicine is recommended based on the set of available medicines and knowledge base.FindingsWe considered four diseases: Hypertension, Gastritis, Alzheimer’s disease, and Parkinson; and performed several experiments for each disease for the different number of available medicines. The execution time to find an alternative medicine (if any) in each case is around four seconds.Originality/valueThe proposed system is cost effective and affordable for most families in India. Although the proposed system is not a substitute of a doctor, this system will enhance the safety golden period for a patient to consult a doctor in the emergency exhaustion of the prescribed medicines.


2021 ◽  
Vol 1 (5) ◽  
pp. 591-597
Author(s):  
Alfyananda Kurnia Putra ◽  
Muhammad Naufal Islam ◽  
Dian Ahmad Sasmito ◽  
Alfa Yusrotin

Learning during the Covid-19 pandemic caused learning activity to be online and causes student’s boredom in Geography. Therefore, teachers must integrating the technology in learning process, with mobile learning (M-Learning) based on mobile context aware systems (MCAS). The study purpose is to determine student’s opinions about implementation of MCAS based M-Learning during the pandemic. This research is a descriptive qualitative with a mix method approach used collection techniques field research and literature study. The results showed that students had a positive opinion regarding the implementation of MCAS based M-Learning during the pandemic, with an average score of 3.40-3.70 out of 4.00. Pembelajaran pada masa pandemi Covid-19 menyebabkan pembelajaran menjadi online sehingga menyebabkan terjadinya kejenuhan siswa dalam proses pembelajaran Geografi. Oleh karena itu, guru harus mampu mengintegrasikan teknologi dalam pembelajaran, melalui mobile learning (M-Learning) berbasis mobile context aware systems (MCAS). Penelitian ini bertujuan mengetahui opini siswa dalam penerapan M-Learning berbasis MCAS pada masa pandemi. Jenis penelitian ini termasuk kualitatif deskriptif dengan pendekatan mix method serta teknik pengumpulan data berupa penelitian lapangan serta studi kepustakaan. Hasil penelitian menunjukkan bahwa siswa memiliki opini positif terkait implementasi M-Learning berbasis MCAS pada masa pandemi, dengan perolehan skor rata-rata skor 3,40-3,70 dari 4,00.


2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Qin Ni ◽  
Ana Belén García Hernando ◽  
Iván Pau de la Cruz

We propose a three-layered context-aware architecture for monitoring activities of daily life in smart home. This architecture provides for the inclusion of functionalities that range from low-level data collection to high-level context knowledge extraction. We have also devised an upper-level ontology to model the context in which the activities take place. This enables having a common activity-related context representation, on which to infer and share knowledge. Furthermore, we have begun to implement a platform that realizes our architecture and ontology, making use of Microsoft’s Lab of Things (LoT) platform, being the preliminary results on this task also described in the paper.


2009 ◽  
Vol 20 (10) ◽  
pp. 2655-2666 ◽  
Author(s):  
Dong LIU ◽  
Xiang-Wu MENG ◽  
Jun-Liang CHEN ◽  
Ya-Mei XIA

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