Using Artificial Intelligence in the Internet of Things

The Internet of Things （IoT） has received much attention over the past decade. With the rapid increase in the use of smart devices, we are now able to collect big data on a daily basis. The data we are gathering （and related problems） are becoming more complex and uncertain. Researchers have therefore turned to artificial intelligence （AI） to efficiently deal with the problems ereated by big data.

Automobile Industry Ushers in Reform and Internet of Intelligences

In recent years,electric vehicles have become popular a mong national governments,sectors and the general public.During January to October of 2017,the production output of China’s new energy vehicles had surpassed 0.5 million units,up over 45%year-on-year.Furthermore,the production output of the whole year is expected to reach 0.7 million units.

ZTE Communications Call for Papers Special Issue on Using Artificial Intelligence in Internet of Things

Internet of Things has received much attention over the past de- cade. With the rapid increase in the use of smart devices, we are now able to collect big data on a daily basis. The data we are gather- ing and related problems are becoming more complex and uncer- tain. Researchers have therefore turned to AI as an efficient way of dealing with the problems created by big data. This special issue of ZTE Communications will be dedicated to development, trends, challenges, and current practices in artificial intelligence for the Internet of Things. Position papers, technology overviews, and case studies are all welcome. Appropriate topics include but are not limited to：

Special Issue on Using Artificial Intelligence in Internet of Things Guest Editors: Fuji Ren, Yu Gu

Interact of Things has received much attention over the past de cade. With the rapid increase in the use of smart devices, we are now able to collect big data on a daily basis. The data we are gather ing and related problems arc becoming more complex and uncer tain. Researchers have therefore turned to AI as an efficient way of dealing with the problems created by big data.

Research on the intelligent internet nursing model based on the child respiratory and asthma control test scale for asthma management of preschool children

BACKGROUND Childhood asthma is a common respiratory ailment that significantly affects preschool children.Effective asthma management in this population is particularly challenging due to limited communication skills in children and the necessity for consistent involvement of a caregiver.With the rise of digital healthcare and the need for innovative interventions,Internet-based models can potentially offer relatively more efficient and patient-tailored care,especially in children.AIM To explore the impact of an intelligent Internet care model based on the child respiratory and asthma control test(TRACK)on asthma management in preschool children.METHODS The study group comprised preschoolers,aged 5 years or younger,that visited the hospital's pediatric outpatient and emergency departments between January 2021 and January 2022.Total of 200 children were evenly and randomly divided into the observation and control groups.The control group received standard treatment in accordance with the 2016 Guidelines for Pediatric Bronchial Asthma and the Global Initiative on Asthma.In addition to above treatment,the observation group was introduced to an intelligent internet nursing model,emphasizing the TRACK scale.Key measures monitored over a six-month period included the frequency of asthma attack,emergency visits,pulmonary function parameters(FEV1,FEV1/FVC,and PEF),monthly TRACK scores,and the SF-12 quality of life assessment.Post-intervention asthma control rates were assessed at six-month follow-up.RESULTS The observation group had fewer asthma attacks and emergency room visits than the control group(P<0.05).After six months of treatment,the children in both groups had higher FEV1,FEV1/FVC,and PEF(P<0.05).Statistically significant differences were observed between the two groups(P<0.05).For six months,children in the observation group had a higher monthly TRACK score than those in the control group(P<0.05).The PCS and MCSSF-12 quality of life scores were relatively higher than those before the nursing period(P<0.05).Furthermore,the groups showed statistically significant differences(P<0.05).The asthma control rate was higher in the observation group than in the control group(P<0.05).CONCLUSION TRACK based Intelligent Internet nursing model may reduce asthma attacks and emergency visits in asthmatic children,improve lung function,quality of life,and the TRACK score and asthma control rate.The effect of nursing was significant,allowing for development of an asthma management model.

I^2oT: Advanced Direction of the Internet of Things

The Internet of Things （IoT） is still in its infancy because of the limited capability of its embedded processor. In the meantime, re- search on artificial intelligence （AI） has made plenty of progress. The application of AI to loT will significantly increase the capa- bilities of IoT, and this will benefit both economic and social development. In this paper, the elementary concepts and key tech- nologies of AI are explained, and the model and principle of intelligent IoT, denoted I^2oT, resulting from the integration of AI and loT are discussed. I^2oT will be the most promising version of IoT. Finally, recommendations for further study and standardization of I2oT are made.

A One-Time Pad Encryption Scheme Based on Efficient Physical-Layer Secret Key Generation for Intelligent IoT System

The one-time pad(OTP)is an applicationlayer encryption technique to achieve the informationtheoretic security,and the physical-layer secret key generation(SKG)technique is a promising candidate to provide the random keys for OTP.In this paper,we propose a joint SKG and OTP encryption scheme with the aid of a reconfigurable intelligent surface(RIS)to boost secret key rate.To maximize the efficiency of secure communication,we divide the process of secure transmission into two stages:SKG and then encrypted packet transmission.Meanwhile,we design an optimal algorithm for allocating time slots for SKG to maximize SKG efficiency without security risk.Furthermore,we design a key updating protocol based on our SKG scheme for OTP encryption.Simulation results verify that our scheme can generate keys securely and efficiently,and significantly improve the secure communication performance in an intelligent IoT system.

A Ray Tracing and Joint Spectrum Based Clustering and Tracking Algorithm for Internet of Intelligent Vehicles

Driven by the rapid growth in information services provided by the Internet and the appearance of new multimedia applications,millimeter wave is foreseen as a key enabler towards the Internet of intelligent vehicles(IoIV)for urban traffic safety enhancement.In this regard,cluster-based channel modeling has become an important research topic in the realm of emergency communications.To fully understand the cluster-based channel model,a series of vehicle-to-infrastructure(V2I)channel simulations at 22.6 GHz are conducted by a three-dimensional ray tracing(RT)simulator.The clustering and tracking algorithm is proposed and analyzed from three aspects by the obtained simulation results.The multiple signal classification estimation spectrum is applied to restrain the influence of antenna sidelobes and identify targets at first.Based on the fundamentals,the clusters can be identified and subsequently tracked using the proposed approach.The impacts of antenna sidelobes,angle resolution of beam rotation,and non-line-of-sight propagation path on the performance of clustering and tracking are evaluated.The multi-component-level RT results are adopted as comparison benchmarks,which reflect the ground truth.This work aims to provide a full picture of the clustering characteristics for designing and analyzing emergency communication systems.