| 1. |
- Abbas, Nadeem, 1980-, et al.
(författare)
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Smart Forest Observatories Network : A MAPE-K Architecture Based Approach for Detecting and Monitoring Forest Damage
- 2023
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Ingår i: Proceedings of the Conference Digital solutions for detecting and monitoring forest damage.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Forests are essential for life, providing various ecological, social, and economic benefits worldwide. However, one of the main challenges faced by the world is the forest damage caused by biotic and abiotic factors. In any case, the forest damages threaten the environment, biodiversity, and ecosystem. Climate change and anthropogenic activities, such as illegal logging and industrial waste, are among the principal elements contributing to forest damage. To achieve the United Nations' Sustainable Development Goals (SDGs) related to forests and climate change, detecting and analyzing forest damages, and taking appropriate measures to prevent or reduce the damages are essential. To that end, we envision establishing a Smart Forest Observatories (SFOs) network, as shown below, which can be either a local area or a wide area network involving remote forests. The basic idea is to use Monitor, Analyze, Plan, Execute, and Knowledge (MAPE-K) architecture from autonomic computing and self-adaptive software systems domain to design and develop the SFOs network. The SFOs are planned to collect, analyze, and share the collected data and analysis results using state-of-the-art methods. The principal objective of the SFOs network is to provide accurate and real-time data to policymakers and forest managers, enabling them to develop effective policies and management strategies for global forest conservation that help to achieve SDGs related to forests and climate change.
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| 2. |
- Ahmedi, Figene, et al.
(författare)
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InWaterSense : An Intelligent Wireless Sensor Network for Monitoring Surface Water Quality to a River in Kosovo
- 2018
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Ingår i: International Journal of Agricultural and Environmental Information Systems. - : IGI Global. - 1947-3192 .- 1947-3206. ; 9:1, s. 39-61
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Tidskriftsartikel (refereegranskat)abstract
- A shift in water monitoring approach from traditional grab sampling to novel wireless sensors is gaining in popularity not only among researchers but also in the market. These latest technologies readily enable numerous advantageous monitoring arrangements like remote, continuous, real-time, and spatially-dense and broad in coverage measurements, and identification of long-term trends of parameters of interest. Thus, a WSN system is implemented in a river in Kosovo as part of the InWaterSense project to monitor its water quality parameters. It is one of the first state of the art technology demonstration systems of its kind in the domain of water monitoring in developing countries like Kosovo. Water quality datasets are transmitted at pre-programmed intervals from sensing stations deployed in the river to the server at university via the GPRS network. Data is then made available through a portal to different target groups (policy-makers, water experts, and citizens). Moreover, the InWaterSense system behaves intelligently like staying in line with water quality regulatory standards.
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| 3. |
- Ahmedi, Figene, et al.
(författare)
-
InWaterSense : An Intelligent Wireless Sensor Network for Monitoring Surface Water Quality to a River in Kosovo
- 2018
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Ingår i: Innovations and Trends in Environmental and Agricultural Informatics. - : IGI Global. - 9781522559788 - 1522559787 - 9781522559795 ; , s. 58-85
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Bokkapitel (refereegranskat)abstract
- A shift in the water monitoring approach from traditional grab sampling to novel wireless sensors is gaining in popularity not only among researchers but also in the market. These latest technologies readily enable numerous advantageous monitoring arrangements like remote, continuous, real-time, and spatially dense and broad in coverage measurements, and identification of long-term trends of parameters of interest. Thus, a WSN system is implemented in a river in Kosovo as part of the InWaterSense project to monitor its water quality parameters. It is one of the first state-of-the-art technology demonstration systems of its kind in the domain of water monitoring in developing countries like Kosovo. Water quality datasets are transmitted at pre-programmed intervals from sensing stations deployed in the river to the server at university via the GPRS network. Data is then made available through a portal to different target groups (policymakers, water experts, and citizens). Moreover, the InWaterSense system behaves intelligently like staying in line with water quality regulatory standards.
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| 4. |
- Alsouda, Yasser, et al.
(författare)
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A Machine Learning Driven IoT Solution for Noise Classification in Smart Cities
- 2018
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Ingår i: Machine Learning Driven Technologies and Architectures for Intelligent Internet of Things (ML-IoT), August 28, 2018, Prague, Czech Republic. - : Euromicro. ; , s. 1-6
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Konferensbidrag (refereegranskat)abstract
- We present a machine learning based method for noise classification using a low-power and inexpensive IoT unit. We use Mel-frequency cepstral coefficients for audio feature extraction and supervised classification algorithms (that is, support vector machine and k-nearest neighbors) for noise classification. We evaluate our approach experimentally with a dataset of about 3000 sound samples grouped in eight sound classes (such as, car horn, jackhammer, or street music). We explore the parameter space of support vector machine and k-nearest neighbors algorithms to estimate the optimal parameter values for classification of sound samples in the dataset under study. We achieve a noise classification accuracy in the range 85% -- 100%. Training and testing of our k-nearest neighbors (k = 1) implementation on Raspberry Pi Zero W is less than a second for a dataset with features of more than 3000 sound samples.
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| 5. |
- Alsouda, Yasser, et al.
(författare)
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IoT-based Urban Noise Identification Using Machine Learning : Performance of SVM, KNN, Bagging, and Random Forest
- 2019
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Ingår i: Proceedings of the International Conference on Omni-Layer Intelligent Systems (COINS '19). - New York : ACM Publications. - 9781450366403 ; , s. 62-67
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Konferensbidrag (refereegranskat)abstract
- Noise is any undesired environmental sound. A sound at the same dB level may be perceived as annoying noise or as pleasant music. Therefore, it is necessary to go beyond the state-of-the-art approaches that measure only the dB level and also identify the type of noise. In this paper, we present a machine learning based method for urban noise identification using an inexpensive IoT unit. We use Mel-frequency cepstral coefficients for audio feature extraction and supervised classification algorithms (that is, support vector machine, k-nearest neighbors, bootstrap aggregation, and random forest) for noise classification. We evaluate our approach experimentally with a data-set of about 3000 sound samples grouped in eight sound classes (such as car horn, jackhammer, or street music). We explore the parameter space of the four algorithms to estimate the optimal parameter values for classification of sound samples in the data-set under study. We achieve a noise classification accuracy in the range 88% - 94%.
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| 6. |
- Amatya, Suyesh, 1982-, et al.
(författare)
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Cross-Platform Mobile Development : Challenges and Opportunities
- 2014. - 1
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Ingår i: ICT Innovations 2013. - Heidelberg : Springer. - 9783319014654 - 9783319014661 ; , s. 219-229
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Bokkapitel (refereegranskat)abstract
- Mobile devices and mobile computing have made tremendous advances and become ubiquitous in the last few years. As a result, the landscape has become seriously fragmented which brings lots of challenges for the mobile development process. Whilst native approach of mobile development still is the predominant way to develop for a particular mobile platform, recently there is shifting towards cross-platform mobile development as well. In this paper, we have performed a survey of the literature to see the trends in cross-platform mobile development over the last few years. With the result of the survey, we argue that the web-based approach and in particular,hybrid approach, of mobile development serves the best for cross-platform development. The results of this work indicate that even though cross platform tools are not fully matured they show great potential. Thus we consider that cross-platform development offers great opportunities for rapid development of high-fidelity prototypes of the mobile application.
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| 7. |
- Bani Hani, Imad, et al.
(författare)
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The Triadic Relationship of Sense-Making, Analytics, and Institutional Influences
- 2022
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Ingår i: Informatics. - : MDPI. - 2227-9709. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- The current business environment demands the enablement of organization-wide use of analytics to support a fact-based decision making. Such movement within the organization require employees to take advantage of the self-service business analytics tools to independently fulfil their needs. However, assuming independence in data analytics requires employees to make sense of several elements which collectively contribute to the generation of required insights. Building on sense-making, self-service business analytics, and institutions literature, this paper explores the relationship between sense-making and self-service business analytics and how institutions influence and shape such relationship. By adopting a qualitative perspective and using 22 interviews, we have empirically investigated a model developed through our literature review and provided more understanding of the sense-making concept in a self-service business analytics context.
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| 8. |
- Bodduluri, Kailash Chowdary, et al.
(författare)
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Dynamic Hybrid Recommendation System for E-Commerce : Overcoming Challenges of Sparse Data and Anonymity
- 2024
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Ingår i: Web Engineering. - : Springer Science+Business Media B.V.. - 9783031623615 ; , s. 435-440
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Konferensbidrag (refereegranskat)abstract
- In the evolving landscape of e-commerce, personalizing user experience through recommendation systems has become a way to boost user satisfaction and engagement. However, small-scale e-commerce platforms struggle with significant challenges, including data sparsity and user anonymity. These issues make it hard to effectively implement recommendation systems, resulting in difficulty in recommending the right products to users. This study introduces an innovative Hybrid Recommendation System (HRS) to address challenges in e-commerce personalization caused by data sparsity and user anonymity. By blending multiple dimensions of the data into one unified system for producing recommendations, this system represents a notable advancement in web engineering for achieving personalized user experiences in the context of limited data. This research emphasizes the significance of innovative and tech-driven solutions in transforming small-scale e-commerce platforms, providing direction for future research and development in the field. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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| 9. |
- Bodduluri, Kailash Chowdary, et al.
(författare)
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Exploring the Landscape of Hybrid Recommendation Systems in E-commerce : A Systematic Literature Review
- 2024
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Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 12, s. 28273-28296
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Forskningsöversikt (refereegranskat)abstract
- This article presents a systematic literature review on hybrid recommendation systems (HRS) in the e-commerce sector, a field characterized by constant innovation and rapid growth. As the complexity and volume of digital data increases, recommendation systems have become essential in guiding customers to services or products that align with their interests. However, the effectiveness of single-architecture recommendation algorithms is often limited by issues such as data sparsity, challenges in understanding user needs, and the cold start problem. Hybridization, which combines multiple algorithms in different methods, has emerged as a dominant solution to these limitations. This approach is utilized in various domains, including e-commerce, where it significantly improves user experience and sales. To capture the recent trends and advancements in HRS within e-commerce over the past six years, we review the state-of-the-art overview of HRS within e-commerce. This review meticulously evaluates existing research, addressing primary inquiries and presenting findings that contribute to evidence-based decision-making, understanding research gaps, and maintaining transparency. The review begins by establishing fundamental concepts, followed by detailed methodologies, findings from addressing the research questions, and exploration of critical aspects of HRS. In summarizing and incorporating existing research, this paper offers valuable insights for researchers and outlines potential avenues for future research, ultimately providing a comprehensive overview of the current state and prospects of HRS in e-commerce.
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| 10. |
- Bodduluri, Kailash Chowdary, et al.
(författare)
-
Exploring the Landscape of Hybrid Recommendation Systems in E-Commerce : A Systematic Literature Review
- 2024
-
Ingår i: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 12, s. 28273-28296
-
Forskningsöversikt (refereegranskat)abstract
- This article presents a systematic literature review on hybrid recommendation systems (HRS) in the e-commerce sector, a field characterized by constant innovation and rapid growth. As the complexity and volume of digital data increases, recommendation systems have become essential in guiding customers to services or products that align with their interests. However, the effectiveness of single-architecture recommendation algorithms is often limited by issues such as data sparsity, challenges in understanding user needs, and the cold start problem. Hybridization, which combines multiple algorithms in different methods, has emerged as a dominant solution to these limitations. This approach is utilized in various domains, including e-commerce, where it significantly improves user experience and sales. To capture the recent trends and advancements in HRS within e-commerce over the past six years, we review the state-of-the-art overview of HRS within e-commerce. This review meticulously evaluates existing research, addressing primary inquiries and presenting findings that contribute to evidence-based decision-making, understanding research gaps, and maintaining transparency. The review begins by establishing fundamental concepts, followed by detailed methodologies, findings from addressing the research questions, and exploration of critical aspects of HRS. In summarizing and incorporating existing research, this paper offers valuable insights for researchers and outlines potential avenues for future research, ultimately providing a comprehensive overview of the current state and prospects of HRS in e-commerce.
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