SMART WATER NETWORK MONITORING: A CASE STUDY AT UNIVERSITI TEKNOLOGI MALAYSIA

Water uses need to be measured, which is critical for evaluating water stress. The Industry 4.0 via the Internet of Things (IoT) and usage of water measurement sensor can provide real-time information on the water flow rate and water pressure, that is crucial for water monitoring and analysis. There is a need for online smart water monitoring that gives out more efficient and sustainable water uses at Universiti Teknologi Malaysia (UTM) campus. A prototype of an online smart water monitoring for UTM, which was developed based on the integration of IoT and Geographical Information System (GIS), consist of four layers; (1) physical layer; (2) network layer; (3) processing layer and, (4) application layer. The findings show that when the water flow increases, the water pressure decreases. When there is no water flow, the lowest value is 52.214 Psi, and the highest value is 60.916 Psi. The latest technology integrating the IoT-GIS for smart water monitoring has shown a very efficient way of providing real-time water parameters information, cost and time effective, and allowing for continuous water consumption analysis via the cloud computing service.

Cloud Computing Service Provider Business Model Success Characteristics

In a digital arena, information technology services provision is shifting to a cloud computing ecosystem. Cloud computing is an enabler for digital transformation with cloud computing service providers central to the digital transformation of both companies and higher education. As cloud computing service providers play the role of an ‘architect' for companies as supply chain is digitised and in supporting higher education institutions striving to deliver user-focused services in the face of increasing competition, an understanding of successful characteristics of cloud computing service provider business models is of main interest for providers and may also be of value for companies and higher education institutions when selecting cloud computing service providers. Despite the importance of cloud computing service providers' business models, information systems literature has provided limited analysis on the characteristics of successful business models. As such, the chapter aims to contribute to the emerging research on characteristics of successful business models.

Effective Decision Making: Data Envelopment Analysis for Efficiency Evaluation in the Cloud Computing Marketplaces

Assessing business performance is a critical issue for practicing managers, and business performance has always been of interest to managers and researchers. In recent years, the world has experienced a rapid growth in the cloud computing service sector thanks to its benefits to business organizations and economic development. Therefore, the performance efficiency of this sector has been concerned as one of the keys in today’s economic environment. This study aimed to assess the performance efficiency of cloud computing service providers in the United States of America, one of the biggest global markets in terms of cloud computing, by applying the data envelopment analysis models. The efficiency of cloud computing providers was evaluated based on the assumption of the non-cooperative game among cloud computing providers in which providers selfishly choose the best strategy to maximize their payoff with three stages. In the first stage, the performance of these providers over the past period was measured by a super slack-based measure. In the second stage, the performance in the future period was predicted by the new data envelopment analysis model: the past–present–future model based on resampling. In the last stage, the efficiency improvement was investigated by adopting the Malmquist productivity index. The findings of this study indicated that the percentage of inefficient providers would increase from 10% in the period from 2017 to 2020 to 20% for 2021 and 2024. Moreover, 30% of providers showed a regress in performance efficiency over the research period of 2017 to 2024. The results of this study provide an insight picture to the decision-makers, and this research will fill the gap in the literature as the first study that measures and predicts the performance efficiency of cloud computing service providers, which will provide a helpful reference for future studies.

Cloud–edge cooperation for meteorological radar big data: a review of data quality control

With the rapid development of information technology construction, increasing specialized data in the field of informatization have become a hot spot for research. Among them, meteorological data, as one of the foundations and core contents of meteorological informatization, is the key production factor of meteorology in the era of digital economy as well as the basis of meteorological services for people and decision-making services. However, the existing centralized cloud computing service model is unable to satisfy the performance demand of low latency, high reliability and high bandwidth for weather data quality control. In addition, strong convective weather is characterized by rapid development, small convective scale and short life cycle, making the complexity of real-time weather data quality control increased to provide timely strong convective weather monitoring services. In order to solve the above problems, this paper proposed the cloud–edge cooperation approach, whose core idea is to effectively combine the advantages of edge computing and cloud computing by taking full advantage of the computing resources distributed at the edge to provide service environment for users to satisfy the real-time demand. The powerful computing and storage resources of the cloud data center are utilized to provide users with massive computing services to fulfill the intensive computing demands.

Does cloud computing influence enterprise performance?

The emergence of the cloud computing service has resulted in the entry of many companies into the market, with numerous competitors for cloud computing leading the technological trend. Recent studies have mainly focused on the characteristics of cloud computing, whereas its influence on firm performance has been rarely discussed. Therefore, this study aimed to fill this empirical research gap. This current study examined whether investments in cloud computing can influence firm performance and whether cloud computing influences firm performance. Data were collected using a questionnaire. Structural equation modeling provided evidence supporting the theoretical model. The results of this study revealed that cloud computing investment influences firm learning and growth performance, internal processes, and finances. The theoretical and practical contributions and implications of these findings are described in this paper.