scholarly journals Intelligent Assistant Decision-Making Method for Power Enterprise Customer Service Based on IoT Data Acquisition

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Rui Xu ◽  
Dan Long ◽  
Jia Liu ◽  
Wanghong Yu ◽  
Lei Xu
Keyword(s):  
Decision Making ◽  
Customer Service ◽  
Data Transmission ◽  
Network Performance ◽  
Real Life ◽  
New Paradigm ◽  
Power Enterprise ◽  
Intelligent Assistant ◽  
Service Data ◽  
Relationship Of

The prevailing era of the Internet of Things (IoT) has renewed all fields of life in general, but, especially with the advent of artificial intelligence (AI), has drawn the attention of researchers into a new paradigm of life standards. This revolution has been accepted around the world for making life comfortable with the use of intelligent devices. AI-enabled machines are more intelligent and capable of completing a specific task which saves a lot of time and resources. Currently, diverse methods are available in the existing literature to handle different issues of real life based on AI and IoT systems. The role of decision-making has its prominence in the AI-enabled and IoT systems. In this article, an AI- and IoT-based intelligent assistant decision-making method is presented for power enterprise customer service. An intelligent model of the customer service data network is designed, and the method of collecting data from IoT to assist decision-making is presented. Then, the semantic relationship of customer service data is defined, and the sharing scope of data transmission and resources are determined to realize intelligent assistant decision-making of customer service in power enterprises. Simulation results show that the proposed method improves the decision data transmission speed and shortens the transmission delay, and the network performance of data interaction is better than that of the existing methods.

scholarly journals AI-Enabled Sensing and Decision-Making for IoT Systems

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Hao Qinxia ◽  
Shah Nazir ◽  
Ma Li ◽  
Habib Ullah ◽  
Wang Lianlian ◽  
...  
Keyword(s):  
Decision Making ◽  
Real Life ◽  
Research Community ◽  
Smart Sensors ◽  
Future Research ◽  
New Paradigm ◽  
Exclusion Criteria ◽  
Intelligent Devices ◽  
Research Questions

The influential stage of Internet of Things (IoT) has reformed all fields of life in general but specifically with the emergence of artificial intelligence (AI) has drawn the attention of researchers into a new paradigm of life standard. This revolution has been accepted around the globe for making life easier with the use of intelligent devices such as smart sensors, actuators, and many other devices. AI-enabled devices are more intelligent and capable of doing a specific task which saves a lot of resources and time. Different approaches are available in the existing literature to tackle diverse issues of real life based on AI and IoT systems. The role of decision-making has its own importance in the AI-enabled and IoT systems. In-depth knowledge of the existing literature is dire need of the research community to summarize the literature in effective way by which practitioners and researchers can benefit from the prevailing proofs and suggest new solutions for solving a particular problem of AI-enabled sensing and decision-making for the IoT system. To facilitate research community, the proposed study presents a systematic literature review of the existing literature, organizes the evidences in a systematic way, and then analyzes it for future research. The study reported the literature of the last 5 years based on the research questions, inclusion and exclusion criteria, and quality assessment of the selected study. Finally, derivations are drawn from the included paper for future research.

scholarly journals Performance of Signal Strength prediction in Data transmission Using Elliott wave Theory

2020 ◽  
Vol 2 (1) ◽  
pp. 62-69
Author(s):  
Balasubramaniam P.M. ◽  
Arivoli S ◽  
Prabhakaran N
Keyword(s):  
Customer Service ◽  
Data Transmission ◽  
Real Life ◽  
Signal Strength ◽  
Wave Theory ◽  
Base Station ◽  
The People ◽  
Strength Based ◽  
Successful Prediction ◽  
Phase Signal

The article describes an algorithm for predicting the future signals with the aid of past signal samples. In the real signal processing environment, the amplitude and unsystematic in phase signal are lead to more complex to estimation the signal, thereby, customer service is enhanced by forecast. The forecast of financial marketplace are usually done by means of Elliot wave theory. In this article possibility and applicability survey of the EW Theory is proposed in the paper towards the power of the signal forecast. In nature, the EW theory has free declining environment, and also uncomfortable based on the customer and base station and height of the antenna. The proposed algorithm has tested in real life conditions, considering both, the pedestrian persons and the people travelling at 60 Km/Hr. Consequently, the predicted result incorporates the practical signal strength based on increasing distribution utility, signal to intervention noise ratio (SNR) and instability at their subsequent time. The end result of the algorithm shows 68% of successful prediction.

E-WOM as a New Paradigm in the Consumer Decision-Making Process

2019 ◽  
pp. 64-81
Author(s):  
Esra Güven ◽  
Volkan Yakin
Keyword(s):  
Decision Making ◽  
Purchase Behavior ◽  
Decision Making Process ◽  
Consumer Decision Making ◽  
New Paradigm ◽  
Consumer Decision ◽  
Five Phases ◽  
Relationship Of ◽  
Post Purchase ◽  
The Impact

Consumer-to-consumer communications in online environments are of a vital importance to the consumer decision-making process. This process consists of five phases, each affected by eWOM communications deeply from the stimulation to the post-purchase behavior. Among all other factors having an impact on this process, the impact of eWOM has a distinguished role. As the technology grows and the consumers use internet and the reviews via internet, they become more and more attached to these reviews to make a purchase decision. In this chapter, the authors make a comprehensive explanation about the consumer decision-making process and explain the relationship of the decision-making phases with eWOM communications.

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