scholarly journals Legal Protection of Artificial Intelligence Data and Algorithms from the Perspective of Internet of Things Resource Sharing

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Na An ◽  
Xiaolei Wang
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Resource Sharing ◽  
Data Privacy ◽  
Legal Protection ◽  
Bullwhip Effect ◽  
Administrative Management ◽  
Effect Model ◽  
Demand Information ◽  
Model Derivation

There are few laws and regulations related to privacy protection in the existing artificial intelligence data sharing environment, lack of practical operability, and low feasibility. The weakening of administrative management and industry self-discipline also reflects my country’s current weak protection of big data privacy. In order to solve the problem of sharing artificial intelligence data and algorithms, it becomes very important to study the legal protection of artificial intelligence data and algorithms from the perspective of Internet of Things resource sharing. This article is aimed at studying the use of laws to protect artificial intelligence data and algorithms. Aiming at reducing the bullwhip effect, a most effective bullwhip effect model derivation algorithm is proposed. This method can not only share customer demand information with members at all levels in the supply chain but also achieve information sharing among members at all levels. Calculate the proportion of the overall time of the program through multiple statistical data ( m = 30 , k = 12 ; and m = 60 , k = 15 ), and extract two special values representing the overall situation ( m = 30 , k = 12 ; m = 60 , k = 15 ). Most of the time consumption of this program is concentrated in the secret distribution stage, accounting for about 80% on average.

IoT ecosystem faces fragmented future

2019 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Supply Chain ◽  
Internet Of Things ◽  
Data Privacy ◽  
The Internet ◽  
Privacy And Security ◽  
Content Type ◽  
Iot Devices ◽  
The Internet Of Things

Subject IoT ecosystem. Significance The market for the Internet of Things (IoT) or connected devices is expanding rapidly, with no manufacturer currently forecast to dominate the supply chain. This has fragmented the emerging IoT ecosystem, triggering questions about interoperability and cybersecurity of IoT devices. Impacts Firms in manufacturing, transportation and logistics and utilities are expected to see the highest IoT spending in coming years. The pace of IoT adoption is inextricably linked to that of related technologies such as 5G, artificial intelligence and cloud computing. Data privacy and security will be the greatest constraint to IoT adoption.

scholarly journals Federated Learning Model with Adaptive Differential Privacy Protection in Medical IoT

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Lina Ni ◽  
Peng Huang ◽  
Yongshan Wei ◽  
Minglei Shu ◽  
Jinquan Zhang
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Data Privacy ◽  
Medical Information ◽  
Differential Privacy ◽  
Training Data ◽  
Security And Privacy ◽  
Good Effect ◽  
Model Parameters ◽  
Personal Privacy

With the proliferation of intelligent services and applications authorized by artificial intelligence, the Internet of Things has penetrated into many aspects of our daily lives, and the medical field is no exception. The medical Internet of Things (MIoT) can be applied to wearable devices, remote diagnosis, mobile medical treatment, and remote monitoring. There is a large amount of medical information in the databases of various medical institutions. Nevertheless, due to the particularity of medical data, it is extremely related to personal privacy, and the data cannot be shared, resulting in data islands. Federated learning (FL), as a distributed collaborative artificial intelligence method, provides a solution. However, FL also involves multiple security and privacy issues. This paper proposes an adaptive Differential Privacy Federated Learning Medical IoT (DPFL-MIoT) model. Specifically, when the user updates the model locally, we propose a differential privacy federated learning deep neural network with adaptive gradient descent (DPFLAGD-DNN) algorithm, which can adaptively add noise to the model parameters according to the characteristics and gradient of the training data. Since privacy leaks often occur in downlink, we present differential privacy federated learning (DP-FL) algorithm where adaptive noise is added to the parameters when the server distributes the parameters. Our method effectively reduces the addition of unnecessary noise, and at the same time, the model has a good effect. Experimental results on real-world data show that our proposed algorithm can effectively protect data privacy.

Utilising internet of things and artificial intelligence to enable twin precision treatment for reversal of type 2 Diabetes

2020 ◽  
Author(s):  
Paramesh Shamanna ◽  
Suresh Damodharan ◽  
Banshi Saboo ◽  
Rajeev Chawla ◽  
Jahangir Mohammed ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Type 2 Diabetes ◽  
Internet Of Things

Innovative Marketing Strategies for Select E-Commerce Companies in India - A Review.

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Amit Kumar Bhanja ◽  
P.C Tripathy
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Business Environment ◽  
Marketing Strategies ◽  
Point Of View ◽  
Digital Marketing ◽  
Customer Base ◽  
Innovative Methods ◽  
Online Shoppers ◽  
Drastic Increase

Innovation is the key to opportunities and growth in today’s competitive and dynamic business environment. It not only nurtures but also provides companies with unique dimensions for constant reinvention of the existing way of performance which enables and facilitates them to reach out to their prospective customers more effectively. It has been estimated by Morgan Stanley that India would have 480 million shoppers buying products online by the year 2026, a drastic increase from 60 million online shoppers in the year 2016. E-commerce companies are aggressively implementing innovative methods of marketing their product offerings using tools like digital marketing, internet of things (IoT)and artificial intelligence to name a few. This paper focuses on outlining the innovative ways of marketing that the E-Commerce sector implements in orders to increase their customer base and aims at determining the future scope of this area. A conceptual comparative study of Amazon and Flipkart helps to determine which marketing strategies are more appealing and beneficial for both the customers and companies point of view.

Sustainable aquaculture development: a review on the roles of cloud computing, internet of things and artificial intelligence (CIA)

2021 ◽  
Author(s):  
Umar Farouk Mustapha ◽  
Abdul‐Wadud Alhassan ◽  
Dong‐Neng Jiang ◽  
Guang‐Li Li
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Sustainable Aquaculture ◽  
Aquaculture Development
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