Autonomic computing investigates how systems can achieve (user) specified control outcomes on their own, without the intervention of a human operator. Autonomic computing fundamentals have been substantially influenced by those of control theory for closed and open-loop systems. In practice, complex systems may exhibit a number of concurrent and inter-dependent control loops. Despite research into autonomic models for managing computer resources, ranging from individual resources (e.g., web servers) to a resource ensemble (e.g., multiple resources within a data center), research into integrating Artificial Intelligence (AI) and Machine Learning (ML) to improve resource autonomy and performance at scale continues to be a fundamental challenge. The integration of AI/ML to achieve such autonomic and self-management of systems can be achieved at different levels of granularity, from full to human-in-the-loop automation. In this article, leading academics, researchers, practitioners, engineers, and scientists in the fields of cloud computing, AI/ML, and quantum computing join to discuss current research and potential future directions for these fields. Further, we discuss challenges and opportunities for leveraging AI and ML in next generation computing for emerging computing paradigms, including cloud, fog, edge, serverless and quantum computing environments. 

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AI for Next Generation Computing: Emerging Trends and Future Directions

https://pure.tue.nl/ws/files/23712271/labeodanon2016.pdf

On the application of wireless sensors and actuators network in existing buildings for occupancy detection and occupancy-driven lighting control

In recent years, maintenance work on public transport routes has drastically decreased in many countries due to difficult economic situations. The various studies that have been conducted by groups of drivers and groups related to road safety concluded that accidents are increasing due to the poor conditions of road surfaces, even affecting the condition of vehicles through costly breakdowns. Currently, the processes of detecting any type of damage to a road are carried out manually or are based on the use of a road vehicle, which incurs a high labor cost. To solve this problem, many research centers are investigating image processing techniques to identify poor-condition road areas using deep learning algorithms. The main objective of this work is to design of a distributed platform that allows the detection of damage to transport routes using drones and to provide the results of the most important classifiers. A case study is presented using a multi-agent system based on PANGEA that coordinates the different parts of the architecture using techniques based on ubiquitous computing. The results obtained by means of the customization of the You Only Look Once (YOLO) v4 classifier are promising, reaching an accuracy of more than 95%. The images used have been published in a dataset for use by the scientific community.

An Architectural Multi-Agent System for a Pavement Monitoring System with Pothole Recognition in UAV Images

Energy Efficiency and Management in Food Processing Facilities

The development of the Internet of Things (IoT) technology has a positive impact on human life. A smart home is one of the IoT technology applications that facilitate human activities. The problem of physical abnormalities is a matter of limited activities for disabled people. This paper proposes a design of IoT-based smart home application with a remote control device that developed using voice commands for disabled people. Smart home control systems help disabled people to control their home electrical devices such as television (TV), lights, and fans using only voice commands without moving to turn on or turn off electrical equipment. The voice recognition on electrical equipment is using the Google Assistant's application on smartphones. The Google Assistant application will accept voice commands when the pronunciation is correct. Voice commands on IoT-based Smart Home are more simple to apply, without typing text messages. Users get convenience compared to using text. The signal strength of an Internet connection will create a useful performance device at the Response Time of Google Assistant, Response Time of System Processing, activating and deactivating Electrical Equipment. We expect that this device could be more useful to help disabled people interact with their environment by utilizing IoT technology facilities.

Design and Implementation of IoT-Based Smart Home Voice Commands for disabled people using Google Assistant

Real-time Traffic Signal Control with Swarm Optimization Methods

In drone applications, the drone could send data using telemetry devices or radio frequency module which has a limited range. So, there is no interaction between user and drone after a certain range. In this study, a hierarchical tree topology based wireless drone network is designed and presented to overcome range challenge. Proposed network consist of three main parts; Control Center (CC), Master Drone (MD) and Slave Drones (SDs). The CC as a network manager communicates with just MD via telemetry devices. SDs are explorer drones for the search and rescue application. The data transfer between CC and SDs is provided by MD which is explorer like SDs. This paper clearly shows that the enhancement of the communication range is possible with such this approach. Also the designed drone networks are simulated using V-REP (Virtual Robot Experimentation Platform). According to the simulation results, the proposed drone network system operates quickly, and finds the target in 5 minutes, which classical system not find in 10 minutes. The proposed model clearly shows that an application using a drone is completed in a shorter time with the drone swarm well organized.

Design and Simulation of the Hierarchical Tree Topology Based Wireless Drone Networks

This paper describes the design and implementation of a wireless home automation system that can be used for general purposes in our life. The proposed system is designed for easy installation, so it could be use at any location to gather indoor conditions. The proposed system comprises of a wireless sensor and actuator network which is low cost and low power. Each wireless sensor node senses and transmits the variations in the local temperature, humidity and luminosity to the cloud database. The cloud server receives the data and stores it in the table and plotting the variations simultaneously. The user web interface provides graphical data analysis. The web of low-power wireless home energy management system allows the temperature, humidity and luminosity variations to be viewed and controlled whenever user want from anywhere in the world. Also, when the large variations in temperature, humidity and luminosity value occur, system will run actuators like heater, cooler, ventilation fan and lighting equipments. It is expected that the proposed system will be more useful in our existing home because of not necessary wire connection and massive energy saving potential.

Internet of Things based smart home system design through wireless sensor/actuator networks

In the past, the Webster optimal cycle time formula was limited to calculate the optimal cycle from historical data for fixed-time traffic signal control. This paper focuses on the design of an adaptive traffic signal control based on fuzzy logic with Webster and modified Webster’s formula. These formulas are used to calculate the optimal cycle time depending on the current traffic situation which applying in the next cycle. The alternation of the traffic condition between two successive cycles is monitored and handled through the fuzzy logic system to compensate the fluctuation. The obtained optimal cycle time is used to determine adaptively the effective phase green times i.e. is used to determine adaptively the maximum allowable extension limit of the green phase in the next cycle. The SUMO traffic simulator is used to compare the results of the proposed adaptive control methods with fuzzy logic-based traffic control, and fixed-time Webster and modified Webster-based traffic control methods. The proposed methods are tested on an isolated intersection. In this study, real field-collected data obtained from three, four, and five approaches intersections in Kilis/Turkey are used to test the performance of the proposed methods. In addition, to examine the efficiency of the proposed techniques at heavy demands, the arbitrary demands are generated by SUMO for a four approaches intersection. The obtained simulation results indicate that the proposed methods overperform the fixed time and fuzzy logic-based traffic control methods in terms of average vehicular delay, speed, and travel time.

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An Adaptive Method for Traffic Signal Control Based on Fuzzy Logic With Webster and Modified Webster Formula Using SUMO Traffic Simulator

Today, increasing costs and environmental concerns have forced to use energy efficiently in the buildings. Universities with high energy consumption have become the focus in order to save energy in the building sector. The efficient use of energy in universities will alleviate the economic burden of energy costs on the university budget as well as an important step for sustainable university criteria. Therefore, in this study, Karamanoglu Mehmetbey University’s (KMU) energy situation was revealed and energy efficiency potential was examined. Firstly, the energy consumption values used in the buildings belonging to KMU settlement were determined, regular measurements were taken using appropriate equipment (thermal camera, flue gas analyzer, ultrasonic flow meter etc.) at energy consumption points and productivity improvement projects were proposed for these points. According to the measurement results, it is determined that the energy consumption value of the university reached to 1422 tons equivalent petrol (TEP) annually and energy saving potential could be obtained up to 18%.

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Seyit Alperen Celtek

Papers

Real-time Traffic Signal Control with Swarm Optimization Methods

Design and Simulation of the Hierarchical Tree Topology Based Wireless Drone Networks

Internet of Things based smart home system design through wireless sensor/actuator networks

An Adaptive Method for Traffic Signal Control Based on Fuzzy Logic With Webster and Modified Webster Formula Using SUMO Traffic Simulator

Üniversite Kampüs Binaları için Enerji Etüdü: Örnek Çalışma