scholarly journals Decision Making in Internet of Things (IoT) : A Systematic Literature Review

2020 ◽  
Vol 5 (1) ◽  
pp. 51-65
Author(s):  
Hespri Yomeldi
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Research Question ◽  
Fog Computing ◽  
The Internet ◽  
New Paradigm ◽  
Decision Making Factors ◽  
Decision Making System ◽  
Machine Communication ◽  
Support Decision Making

Today’s internet technologies support everything that human do. By using integrated technologies the things that connected to internet can provide data. The Internet of Things (IoT) is the new paradigm in provide the data without human communicated. The IoT system support machine to machine communication that can be used to develop smart services that can generate a lot of data. This exponential data can support a decision making. The decision making system depend on availability and reliability of data. This study focus to how the Internet of Thing support decision making system. With a survey of literature to understand the trends, models and factors of decision making in IoT based on previous research. This survey following step by conduct the research question (RQ), then search and observation the previous research from database journal. Based on reviewing 26 articles, this study conclude that the trends of decision making in IoT are implemented on Manufacturing and Industry, Healthcare, Agriculture and Transportation. Besides that the decision model that can support by IoT used Fog Computing,  Fuzzy, Game Theoritic, Clustering Based on Multimodal Data Correlation, etc. Meanwhile the decision making factors that influenced by IoT like Latency, data-driven, security, data reliability and accurate.  The integrated of model and point of interest on decision making in IoT should be improved.  It will be the opportunities and challenge in IoT to support decision making in future.

scholarly journals Sistem Pendukung Keputusan Penerangan Ruangan Berbasis IoT Menggunakan Protokol MQTT dan Fuzzy Tsukamoto

2020 ◽  
Vol 2 (2) ◽  
pp. 304-313
Author(s):  
Ahmad Fauzan Hakim ◽  
Wirarama Wedhaswara ◽  
Ahmad Zafrullah Mardiansyah
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Light Intensity ◽  
The Internet ◽  
Light Conditions ◽  
Light Bulb ◽  
Application Program ◽  
Inappropriate Use ◽  
Decision Making System ◽  
The Internet Of Things

Inappropriate use of a light bulb in light conditions in the room causes electricity to go to waste. To conserve electricity and keep the lights from breaking quickly, it needs to be done to measure the condition of the light around the lamp. For that it requires a decision-making system of the lighting room based on the Internet of things and using MQTT protocol and fuzzy tsukamoto logic methods. The MQTT protocol used is CloudMQTT to store data or be called a broker. CloudMQTT has 4 important instance info, that is server, user, password, and port. 4. That instance info is used to connect the application program with the broker in order for the system to subscribe and publish from broker to application. For fuzzy tsukamoto combination of rules built up from the three functions of membership, that is the intensity of light, time, and the condition of the light. A combination of rules from two variables is light intensity and time generates 20 combinations of rules. Deffuzification on fuzzy tsukamoto earned by taking a centralized average.

scholarly journals Processing Complex Events in Fog-Based Internet of Things Systems for Smart Agriculture

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7226
Author(s):  
Sandy F. da Costa Bezerra ◽  
Airton S. M. Filho ◽  
Flavia C. Delicato ◽  
Atslands R. da Rocha
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Fog Computing ◽  
Complex Event Processing ◽  
The Internet ◽  
Event Processing ◽  
Data Traffic ◽  
Hierarchical Processing ◽  
Computing Paradigm ◽  
The Internet Of Things

The recent growth of the Internet of Things’ services and applications has increased data processing and storage requirements. The Edge computing concept aims to leverage the processing capabilities of the IoT and other devices placed at the edge of the network. One embodiment of this paradigm is Fog computing, which provides an intermediate and often hierarchical processing tier between the data sources and the remote Cloud. Among the major benefits of this concept, the end-to-end latency can be decreased, thus favoring time-sensitive applications. Moreover, the data traffic at the network core and the Cloud computing workload can be reduced. Combining the Fog computing paradigm with Complex Event Processing (CEP) and data fusion techniques has excellent potential for generating valuable knowledge and aiding decision-making processes in the Internet of Things’ systems. In this context, we propose a multi-tier complex event processing approach (sensor node, Fog, and Cloud) that promotes fast decision making and is based on information with 98% accuracy. The experiments show a reduction of 77% in the average time of sending messages in the network. In addition, we achieved a reduction of 82% in data traffic.

HEALTH TECHNOLOGY ASSESSMENT AND PERSONALIZED MEDICINE: ARE ECONOMIC EVALUATION GUIDELINES SUFFICIENT TO SUPPORT DECISION MAKING?

2014 ◽  
Vol 30 (2) ◽  
pp. 179-187 ◽  
Author(s):  
Don Husereau ◽  
Deborah A. Marshall ◽  
Adrian R. Levy ◽  
Stuart Peacock ◽  
Jeffrey S. Hoch
Keyword(s):  
Decision Making ◽  
Economic Evaluation ◽  
Personalized Medicine ◽  
Health Technology Assessment ◽  
Technology Assessment ◽  
Health Technology ◽  
Population Based ◽  
New Paradigm ◽  
Current Guidance ◽  
Support Decision Making

Background: Many jurisdictions delivering health care, including Canada, have developed guidance for conducting economic evaluation, often in the service of larger health technology assessment (HTA) and reimbursement processes. Like any health intervention, personalized medical (PM) interventions have costs and consequences that must be considered by reimbursement authorities with limited resources. However, current approaches to economic evaluation to support decision making have been largely developed from population-based approaches to therapy—that is, evaluating the costs and consequences of single interventions across single populations. This raises the issue as to whether these methods, as they are or more refined, are adequate to address more targeted approaches to therapy, or whether a new paradigm for assessing value in PM is required.Objectives: We describe specific issues relevant to the economic evaluation of diagnostics-based PM and assess whether current guidance for economic evaluation is sufficient to support decision making for PM interventions.Methods: Issues were identified through literature review and informal interviews with national and international experts (n = 10) in these analyses. This article elaborates on findings and discussion at a workshop held in Ottawa, Canada, in January 2012.Results: Specific issues related to better guiding economic evaluation of personalized medicine interventions include: how study questions are developed, populations are characterized, comparators are defined, effectiveness is evaluated, outcomes are valued and how resources are measured. Diagnostics-based PM also highlights the need for analyses outside of economic evaluation to support decision making.Conclusions: The consensus of this group of experts is that the economic evaluation of diagnostics-based PM may not require a new paradigm. However, greater complexity means that existing approaches and tools may require improvement to undertake these more analyses.

scholarly journals IoT Based Decision Making System to Improve Veracity of Big Data

2018 ◽  
Vol 7 (3.1) ◽  
pp. 63 ◽  
Author(s):  
R Revathy ◽  
R Aroul Canessane
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Internet Of Things ◽  
Data Streams ◽  
Data Cleaning ◽  
Data Handling ◽  
Secure Data ◽  
Decision Making System ◽  
Data Investigation ◽  
Impact Data

Data are vital to help decision making. On the off chance that data have low veracity, choices are not liable to be sound. Internet of Things (IoT) quality rates big data with error, irregularity, deficiency, trickery, and model guess. Improving data veracity is critical to address these difficulties. In this article, we condense the key qualities and difficulties of IoT, which impact data handling and decision making. We audit the scene of estimating and upgrading data veracity and mining indeterminate data streams. Also, we propose five suggestions for future advancement of veracious big IoT data investigation that are identified with the heterogeneous and appropriated nature of IoT data, self-governing basic leadership, setting mindful and area streamlined philosophies, data cleaning and handling procedures for IoT edge gadgets, and protection safeguarding, customized, and secure data administration.  

scholarly journals Guest Editorial Special Issue on Fog Computing in the Internet of Things

2017 ◽  
Vol 4 (5) ◽  
pp. 1113-1116 ◽  
Author(s):  
Rong N. Chang ◽  
Xiuzhen Cheng ◽  
Wei Cheng ◽  
Wonjun Lee ◽  
Yingshu Li ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Guest Editorial ◽  
Fog Computing ◽  
The Internet ◽  
Special Issue ◽  
Editorial Special Issue ◽  
The Internet Of Things
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