Sharif Digital Repository

We propose a novel hybrid learning approach to gain situation awareness in smart environments by introducing a new situation identifier that combines an expert system and a machine learning approach. Traditionally, expert systems and machine learning approaches have been widely used independently to detect ongoing situations as the main functionality in smart environments in various domains. Expert systems lack the functionality to adapt the system to each user and are expensive to design based on each setting. On the other hand, machine learning approaches fail in the challenge of cold start and making explainable decisions. Using both of these approaches enables the system to use user's... 

Aerial firefighting plays an integral role in containing wildfires, which have been growing rapidly in frequency and intensity over the past decades. However, the current aerial-resource management models were developed decades ago, based on the technology available then. This research aims to investigate how and what modern technologies can be integrated into aerial firefighting operation to help it keep up with the worsening situation. DSM has been used as an engineering tool to decompose the complex problem space into separate manageable segments. Using a task-based DSM, the interdependencies which give rise to unnecessary complexities are visualized, and the potential to integrate new... 

To understand how aerial accidents occur, the installation of flight data recorders (FDR) and cockpit voice recorders (CVR) have become mandatory by law. However, such devices play a passive role and are used once an accident has occurred. Recent advances in machine learning techniques and their application in solving engineering problems are the keys to creating a more active role for both FDR as well as CVR. Here, we investigate a new approach to bringing intelligence to an FDR (called I-FDR). Through a continuous data-mining process, an I-FDR could bring better situational awareness to the flight crew. An I-FDR, similar to the FDR, records all pertinent flying parameters. In addition,... 

Monitoring/control infrastructures are often assumed to be fully reliable in power system reliability studies. However, recent investigations on blackouts have revealed the crucial impacts of monitoring/control system malfunctions. This paper addresses the impact of situational awareness and controllability on power system reliability assessment. A methodology is proposed to simulate a situation in which a limitation of either or both monitoring and control functions could spread the consequence of power system events throughout the grid. It is assumed that the monitoring/control infrastructure is based on a wide-area measurement system (WAMS). While the proposed methodology is applicable to... 

Monitoring/control infrastructures are often assumed to be fully reliable in power system reliability studies. However, recent investigations on blackouts have revealed the crucial impacts of monitoring/control system malfunctions. This paper addresses the impact of situational awareness and controllability on power system reliability assessment. A methodology is proposed to simulate a situation in which a limitation of either or both monitoring and control functions could spread the consequence of power system events throughout the grid. It is assumed that the monitoring/control infrastructure is based on a wide-area measurement system (WAMS). While the proposed methodology is applicable to... 

One of the most concerning problems in Smart Grids is the lack of a proper data acquisition system with high security, desired flexibility and required network capacity. These demands prove the vital role of communications in conjunction with smart girds. In this paper, Wireless Sensor Networks are proposed as a compatible choice for satisfying these requirements. However, Wireless Sensor Networks utilized for smart grids necessitate some specifications. We will study these specifications and suggest viable manipulations in the architecture of sensor nodes and network topology. Furthermore, after analyzing the properties of various communication systems, an appropriate choice is included in... 

The development of smart meters enables situational awareness in electric power distribution systems. The situational awareness provides significant advantages such as line outage and electricity theft detection. This paper aims at using smart meter data to detect these anomalies. To do so, an appropriate cluster-based method as an unsupervised machine learning approach is applied. A stochastic method based on conditional correlation is also proposed to localize the anomalies. It is shown that this can be done by detecting changes in bus connections using present and historical smart meter data. Therefore, network topology inspection can be avoided if the proposed method is applied. A...