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Author: search.filters.author.Chotiphan, SupannadaHas files: No

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    Item type:Publication,
    Development of WLAN Topology Display System
    (2023-01-01)
    Wongwirat, Olarn
    ;
    Chotiphan, Supannada
    ;
    Hongtong, Tadchapon
    ;
    Suttijumnong, Nattawat
    Currently, packet sniffer tools can capture packets and provide information for monitoring, analyzing, and troubleshooting networks, e.g., traffic, bandwidth, protocol, etc. However, these tools lack the capability, or feature, to display a network topology diagram on the screen, particularly for a WLAN (Wireless Local Area Network), which is different from expensive network monitoring software sold commercially in the market. Therefore, it is difficult for a network administrator to visualize which client is connected to which AP (Access point) in the service areas of WLAN, or hotspots, for monitoring. This paper presents the development of the WLAN topology display system to support the network administrator in monitoring and enhancing the network services in the future. The system acquires the packet data captured by the packet sniffer tool, i.e., Wireshark. Then, the packet information is analyzed by using the data from the MAC (Medium Access Control) header following the IEEE802.11 standard to find the types, connection modes, and MAC addresses. Finally, the mapping table associated with the connected devices, i.e., client stations and APs, is constructed and used to create the WLAN topology diagram to display on the screen. The prototype system is implemented and tested in the laboratory environment, and the WLAN topology diagram showing the connections between the clients and the APs can be displayed on screen accurately as required.
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    Adapted ACO Algorithm for Energy-Efficient Path Finding of Waste Collection Robot
    (2022-01-01)
    Tomitagawa, Koki
    ;
    Anuntachai, Anuntapat
    ;
    Chotiphan, Supannada
    ;
    Wongwirat, Olarn
    ;
    Kuchii, Shigeru
    Waste collection is a major concern of many companies with large areas of facility, e.g., buildings or factories, where there are many trash bins at various dumping points. Therefore, they require human labor to handle, which is a major cost of consideration. Currently, there are research works using robots for waste collection instead of humans. There is a challenge for waste collection robots in terms of energy consumption to pick up the waste at various dumping points efficiently. The factors related to the energy consumption of waste collection robots are directly related to the distance and waste weight that the robots have to collect and carry from the trash bins at various dump points along the paths. This paper presents the adapted ant colony optimization (ACO) algorithm to find the energy-efficient paths of the waste collection robots. The adapted ACO algorithm uses the waste weight in the trash bin as path heuristic information between two dumping points to determine the state transition probability for finding the most energy-efficient path. The experiment was conducted by the simulation to compare the result with the conventional ACO algorithm that uses distance as the path heuristic information. The simulation results expressed that the adapted ACO algorithm provided the most energy-efficient path under the number of nodes and waste weights specified better than the conventional ACO algorithm.
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    Energy optimal path finding for waste collection robot using ant colony optimization algorithm
    (2021-01-01)
    Tomitagawa, Koki
    ;
    Chotiphan, Supannada
    ;
    Kuchii, Shigeru
    ;
    Anuntachai, Anuntapat
    ;
    Wongwirat, Olarn
    Solid Waste Management (SWM) has always been an important consideration for any country, and among the operational steps of SWM, Solid Waste Collection (SWC) has become one of the most challenging ones. Currently, most of the vehicles used for waste collection require workers and have the problem of emitting CO2. Compared to waste collection by vehicles, waste collection using mobile robots has the advantage of not consuming personnel and not emitting CO2, which is harmful to the environment. However, while mobile robots can solve the shortage of manpower and environmental problems, they also have the problem of limited energy resources. In order for mobile robots to collect waste more efficiently, we designed the waste collection problem as a Capacitated Vehicle Routing Problem (CVRP) and optimized it using the Ant Colony Optimization (ACO) algorithm. The ACO algorithm proposed in this study focuses on the energy consumption of the mobile robot performing waste collection and searches for a route with less energy consumption by using the waste weight as the weighting factor. The preliminary performance verification of the proposed method is compared with the existing conventional ACO algorithm using the CVRP benchmark.