MANAJEMEN PENGETAHUAN UNTUK RISIKO BENCANA TSUNAMI –LITERATURE REVIEW

The application of knowledge management (KM) using Internet of Things (IoT) and Artificial Intelligence (AI) technology is able to capture, store, and disseminate disaster information in all phases of the tsunami disaster. IoT promises to provide continuous fast data, AI used in several disaster risk management applications promises to automate the analysis and dissemination of potential disaster information, as well as the results of disaster event analysis more accurately and faster. This study aims to develop an AI and IoT-based KM model for tsunami risk management based on the comparative results of previous research. The results of the comparison show that most KM, AI, and IoT research focus on the process of knowledge capture, knowledge store, knowledge sharing and mostly focus on pre-disaster. Some other KM research focuses on KM systems without AI, and IoT on the process of knowledge capture, knowledge store, knowledge sharing and only focuses on the stage of a disaster. There is very limited KM research that simultaneously examines KMS, AI, IoT in all knowledge management processes for all stages of tsunami disaster risk. The results of the comparison utilize to develop AI and IoT-based KM models for all stages of tsunami disaster risk management. This study can be a good guidance for stakeholders on the application of AI-based KM and IoT technology to manage tsunami disaster risk in Indonesia.Penerapan manajemen pengetahuan atau knowledge management (KM) dengan menggunakan Teknologi Internet of Things (IoT) dan Artificial Intelligence (AI) mampu menangkap, menyimpan, dan menyebarluaskan informasi kebencanaan pada semua fase bencana tsunami. IoT menjanjikan penyediaan data secara terus menerus dan cepat, AI yang digunakan dalam beberapa aplikasi manajemen risiko bencana menjanjikan otomasi analisis dan penyebarluasan informasi potensi bencana, maupun hasil analisis kejadian bencana dengan lebih akurat dan lebih cepat. Penelitian ini bertujuan untuk menyusun model KM berbasis AI dan IoT untuk manajemen risiko tsunami berdasarkan hasil komparasi penelitian yang sudah dilakukan sebelumnya. Hasil komparasi menunjukkan bahwa sebagian besar penelitian KM, AI, dan IoT fokus pada proses knowledge capture, knowledge store, knowledge sharing dan hanya fokus pada tahan pra bencana. Sebagian penelitian KM lainnya hanya fokus pada Sistem KM tanpa AI, dan IoT pada proses knowledge capture, knowledge store, knowledge sharing dan hanya fokus pada tahap ketika bencana. Belum ada penelitian KM yang sekaligus meneliti KMS, AI, IoT pada semua proses manajemen pengetahuan untuk semua tahapan risiko bencana tsunami. Hasil komparasi menjadi bahan untuk membangun model KM berbasis AI dan IoT untuk semua tahapan manajemen risiko bencana tsunami. Studi ini dapat menjadi panduan yang baik bagi pemangku kepentingan tentang penerapan KM berbasis AI dan teknologi IoT untuk mengelola risiko bencana tsunami di Indonesia

The Internet of Things for Natural Risk Management (Inte.Ri.M.)

This chapter deals with the development of a management system, which integrates the use of IoT in natural risk detection, revention, and management with economic evaluation of each stage. In the introductory part, recent data are presented that document the importance that natural disasters have for the environment and for the Italian economy. Section 2 presents the Inte.Ri.M. project—the Internet of Things for Natural Risk Management—its purpose, activity plan, and bodies involved. Technical aspects are treated in Section 3 with the choice of hardware and software components and the solutions for collecting and transmitting data. Section 4 is about the economic aspects considering the stages of prevention, intervention, and restoration and the relation between the intensity of human activity and environment to define a range of situations. These scenarios call for different economic methodologies useful to estimate economic implications of each stage in the short, medium, and long term. Section 5 describes the structure of the Inte.Ri.M. management system and the foreseen functionalities. In the conclusion, the critical points are discussed, and the steps for the transposition of the work carried out on the territory are outlined, according to the provisions of the work program

Power Consumption Analysis, Measurement, Management, and Issues:A State-of-the-Art Review of Smartphone Battery and Energy Usage

The advancement and popularity of smartphones have made it an essential and all-purpose device. But lack of advancement in battery technology has held back its optimum potential. Therefore, considering its scarcity, optimal use and efficient management of energy are crucial in a smartphone. For that, a fair understanding of a smartphone's energy consumption factors is necessary for both users and device manufacturers, along with other stakeholders in the smartphone ecosystem. It is important to assess how much of the device's energy is consumed by which components and under what circumstances. This paper provides a generalized, but detailed analysis of the power consumption causes (internal and external) of a smartphone and also offers suggestive measures to minimize the consumption for each factor. The main contribution of this paper is four comprehensive literature reviews on: 1) smartphone's power consumption assessment and estimation (including power consumption analysis and modelling); 2) power consumption management for smartphones (including energy-saving methods and techniques); 3) state-of-the-art of the research and commercial developments of smartphone batteries (including alternative power sources); and 4) mitigating the hazardous issues of smartphones' batteries (with a details explanation of the issues). The research works are further subcategorized based on different research and solution approaches. A good number of recent empirical research works are considered for this comprehensive review, and each of them is succinctly analysed and discussed