• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.93-102
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• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.113-122
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• 2024

Recently, cutting-edge ICT technologies such as artificial intelligence, blockchain, edge computing, and the Internet of Things have been applied in various fields to create new services and a new digital era. Along with these technological developments, various policies are being implemented in Korea to transform the country from a "Smart City" to a "Platform City". We can create new services and values by linking with the Smart City Integrated Platform and Smart Housing Platform. This paper defines a linkage scenario between a Smart Housing Platform and the Smart 119 Emergency Dispatch Support Service, one of the Smart City Safety Nets. We propose a data transmission protocol and a metadata schema for data exchange between the Smart Housing Platform and the Smart City Integrated Platform to provide the Smart 119 Emergency Dispatch Support Service.