A practical framework for data collection in wireless sensor networks

Optimizing energy consumption for extending the lifetime in wireless sensor networks is of dominant importance. Groups of autonomous robots and unmanned aerial vehicles (UAVs) acting as mobile data collectors are utilized to minimize the energy expenditure of the sensor nodes by approaching the sensors and collecting their buffers via single hop communication, rather than using multihop routing to forward the buffers to the base station. This paper models the sensor network and the mobile collectors as a system-of-systems, and defines all levels and types of interactions. A practical framework that facilitates deploying heterogeneous mobiles without prior knowledge about the sensor network is presented. Realizing the framework is done through simulation experiments and tested against several performance metrics.<br /

Optimal multisensor data fusion for linear systems with missing measurements

Multisensor data fusion has attracted a lot of research in recent years. It has been widely used in many applications especially military applications for target tracking and identification. In this paper, we will handle the multisensor data fusion problem for systems suffering from the possibility of missing measurements. We present the optimal recursive fusion filter for measurements obtained from two sensors subject to random intermittent measurements. The noise covariance in the observation process is allowed to be singular which requires the use of generalized inverse. Illustration example shows the effectiveness of the proposed filter in the measurements loss case compared to the available optimal linear fusion methods.<br /

Airport and air cargo operation systems

Analysis of airport and air cargo operations is commonly performed in isolation, sharing only simple information such as flight schedules. Systems theory and Systems methodology can enhance such analysis by considering all aspects of air operations. It provides the decision-maker with an improved understanding of the implication of policy decisions, resource allocations and infrastructure investment strategies, through the capture of emergent behaviours and interdependencies. For example, the term airport operations, initially reminds us of the thought of passengers being transported by aircraft. Deeper thinking would identify activities that affect passenger operations, such as baggage handling systems, aircraft maintenance, and passenger security. In reality, airport operations consist of numerous aspects, including; concourses, runways, airlines, fuel depots, cargo terminal operators, retail, parking, cleaning, catering and many interacting people including travellers, service providers and visitors. For the airport to function effectively, these numerous systems must work together. This talk will focus on new tools and methodologies that are required for model development and analysis. It will then focus on modelling, simulation and analysis of the airport operations, providing greater understanding of airport operation with an emphasis towards security

A control methodology for automated manufacturing

The application of computers in the manufacturing industry has substantially altered the control procedures used to program a whole manufacturing process. Currently, one the problems which automated manufacturing systems are experiencing is the lack of a good overall control system. The subject of this research has been centred on the identification of the problems involved in current methods of control and their advantages and disadvantages in an automated manufacturing system. As a result, a different type of control system has been proposed which distributes both the control and the decision making. This control model is an hybrid of hierarchical and hierarchical control systems which takes advantage of the best points offered by both types of control structures. The Durham FMS rig has been used as a testbed for an automated manufacturing system to which the hybrid control system has been applied. The implementation of this control system would not have been possible without the design and development of a System Integration Tool (SIT). The system is capable of real-time scheduling of the system activities. Activities within the system are monitored in real-time and a recording of the system events is available, which allows the user to analyse the activities of the system off-line. A network independent communication technique was developed for the Durham FMS which allowed the manufacturing cells to exercise peer-to-peer communication. The SIT also allowed the integration of equipment from different vendors in the FMS

A life cycle inventory of aluminium die casting

As part of an ongoing project, a life cycle inventory (LCI) of aluminium high pressure die casting (HPDC) has been collected. This has been conducted from the view of an individual product and also the entire process. The objective of the study was to analyse the process and suggest changes to reduce environmental impacts. One modem aluminium high pressure die casting plant located in Victoria, Australia was evaluated and modelled. Site specific data on energy and materials was gathered and the process was modelled using a typical automotive component. The paper also presents our experience and methodology used in this inventory data collection process from the real industry for LCA purposes. The inventory data collected itself reveals that the HPDC process is energy intensive and as such the major emissions were from the use of natural gas fired furnaces and from the brown coal derived electricity. It is also found the large environmental benefits of using secondary aluminium over primary aluminium in the HPDC process. A detailed LCA is being cal1ied out based on the inventory obtained.</div

Decentralized mobility models for data collection in wireless sensor networks

Controlled mobility in wireless sensor networks provides many benefits towards enhancing the network performance and prolonging its lifetime. Mobile elements, acting as mechanical data carriers, traverse the network collecting data using single-hop communication, instead of the more energy demanding multi-hop routing to the sink. Scaling up from single to multiple mobiles is based more on the mobility models and the coordination methodology rather than increasing the number of mobile elements in the network. This work addresses the problem of designing and coordinating decentralized mobile elements for scheduling data collection in wireless sensor networks, while preserving some performance measures, such as latency and amount of data collected. We propose two mobility models governing the behaviour of the mobile element, where the incoming data collection requests are scheduled to service according to bidding strategies to determine the winner element. Simulations are run to measure the performance of the proposed mobility models subject to the network size and the number of mobile elements.<br /

Multi-Agent Deep Reinforcement Learning with Human Strategies

Deep learning has enabled traditional reinforcement learning methods to deal with high-dimensional problems. However, one of the disadvantages of deep reinforcement learning methods is the limited exploration capacity of learning agents. In this paper, we introduce an approach that integrates human strategies to increase the exploration capacity of multiple deep reinforcement learning agents. We also report the development of our own multi-agent environment called Multiple Tank Defence to simulate the proposed approach. The results show the significant performance improvement of multiple agents that have learned cooperatively with human strategies. This implies that there is a critical need for human intellect teamed with machines to solve complex problems. In addition, the success of this simulation indicates that our multi-agent environment can be used as a testbed platform to develop and validate other multi-agent control algorithms.Comment: 2019 IEEE International Conference on Industrial Technology (ICIT), Melbourne, Australi

Kanban devs modelling, simulation and verification

Kanban Control Systems (KCS) have become a widely accepted form of inventory and production control. The creation of realistic Discrete Events Simulation (DES) models of KCS require specification of both information and material flow. There are several commercially available simulation packages that are able to model these systems although the use of an application specific modelling language provides means for rapid model development. A new Kanban specific simulation language as well as a high-speed execution engine is verified in this paper through the simulation of a single stage single part type production line. A single stage single part KCS is modelled with exhaustive enumeration of the decision variables of container sizes and number of Kanbans. Several performance measures were used; 95% Confidence Interval (CI) of container Flow Time (FT), mean line throughput as well as the Coefficient of Variance (CV) of FT and Cycle Time were used to determine the robustness of the control system.<br /