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Malka N. Halgamuge

Other affiliations: King's College London, RMIT University, Charles Sturt University  ...read more
Bio: Malka N. Halgamuge is an academic researcher from University of Melbourne. The author has contributed to research in topics: Wireless sensor network & Key distribution in wireless sensor networks. The author has an hindex of 20, co-authored 129 publications receiving 1492 citations. Previous affiliations of Malka N. Halgamuge include King's College London & RMIT University.


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Journal ArticleDOI
TL;DR: The model is used to evaluate energy consumption and node lifetime for a sensor network with fixed configuration and it is shown that existing energy models over-estimate life expectancy of a sensor node by 30-58% and also yield an "optimised" number of clusters which is too large.
Abstract: A comprehensive energy model for wireless sensor networks is provided by considering seven key energy consumption sources some of which are ignored by currently available models. We demonstrate the importance of using such a comprehensive model by comparing it to other existing energy models in terms of the lifetime of a sensor node. We use our model to evaluate energy consumption and node lifetime for a sensor network with fixed configuration and we validate this evaluation by simulation. We show that existing energy models over-estimate life expectancy of a sensor node by 30-58% and also yield an "optimised" number of clusters which is too large. We further make the following two observations: 1) the optimal number of clusters increases with the increase of free space fading energy, 2) for sensor networks with 100 sensors over an area of 10 4 -10 5 (m 2 ), finding the optimal number of clusters becomes less important when free space fading energy is very low (less than 1670 pJ/bit/m 2 ), while for larger networks, on the other hand, cluster optimization is still important even if free space fading energy is low. Guidelines for efficient and reliable sensor network design as well as extension to a sensor network with rotating cluster heads are provided.

220 citations

Journal ArticleDOI
TL;DR: The aim to analyze recently developed IoT applications in the agriculture and farming industries to provide an overview of sensor data collections, technologies, and sub-verticals such as water management and crop management and provide recommendations for future research to include IoT systems' scalability, heterogeneity aspects, IoT system architecture, data analysis methods, size or scale of the observed land or agricultural domain.
Abstract: It is essential to increase the productivity of agricultural and farming processes to improve yields and cost-effectiveness with new technology such as the Internet of Things (IoT). In particular, IoT can make agricultural and farming industry processes more efficient by reducing human intervention through automation. In this study, the aim to analyze recently developed IoT applications in the agriculture and farming industries to provide an overview of sensor data collections, technologies, and sub-verticals such as water management and crop management. In this review, data is extracted from 60 peer-reviewed scientific publications (2016-2018) with a focus on IoT sub-verticals and sensor data collection for measurements to make accurate decisions. Our results from the reported studies show water management is the highest sub-vertical (28.08%) followed by crop management (14.60%) then smart farming (10.11%). From the data collection, livestock management and irrigation management resulted in the same percentage (5.61%). In regard to sensor data collection, the highest result was for the measurement of environmental temperature (24.87%) and environmental humidity (19.79%). There are also some other sensor data regarding soil moisture (15.73%) and soil pH (7.61%). Research indicates that of the technologies used in IoT application development, Wi-Fi is the most frequently used (30.27%) followed by mobile technology (21.10%). As per our review of the research, we can conclude that the agricultural sector (76.1%) is researched considerably more than compared to the farming sector (23.8%). This study should be used as a reference for members of the agricultural industry to improve and develop the use of IoT to enhance agricultural production efficiencies. This study also provides recommendations for future research to include IoT systems' scalability, heterogeneity aspects, IoT system architecture, data analysis methods, size or scale of the observed land or agricultural domain, IoT security and threat solutions/protocols, operational technology, data storage, cloud platform, and power supplies.

105 citations

Journal ArticleDOI
TL;DR: The results show that system identification enables automation while incorporating direct measurements to MPC enabling automation, and MPC shows to be a promising tool for irrigation control.
Abstract: This research proposes A THEORETICAL FRAMEWORK based on model predictive control (MPC) for irrigation control to minimize both root zone soil moisture deficit (RZSMD) and irrigation amount under a limited water supply. We (i) investigate means to incorporate direct measurements to MPC (ii) introduce two Robust MPC techniques - Certainty Equivalence control (CE) and Disturbance Affine Feedback Control (DA) - to mitigate the uncertainty of weather forecasts, and (iii) provide conditions to obtain two important theoretical aspects of MPC - feasibility and stability - in the context of irrigation control. Our results show that system identification enables automation while incorporating direct measurements. Both DA and CE minimize RZSMD and irrigation amount under uncertain weather forecasts and always maintain soil moisture above wilting point subject to water availability. The theoretical results are compared against the model AQUACROP, weather data and forecasts from Shepparton, Australia. We also discuss the performance of Robust MPC under different water availability, soil, crop conditions. In general, MPC shows to be a promising tool for irrigation control. MPC is used to minimize both root zone soil moisture deficit and irrigation amount.System identification incorporates direct measurements to MPC enabling automation.Uncertainty in weather forecasts is mitigated using two modified Robust MPC approaches.Optimal operation can be guaranteed through the proposed method.Guaranteed operation above wilting point at all times subject to water availability.

74 citations

Proceedings ArticleDOI
02 Apr 2003
TL;DR: Energy optimized cluster formation for a set of randomly scattered wireless sensors is presented and the clustering is driven by the minimization of energy for all the sensors.
Abstract: Energy optimized cluster formation for a set of randomly scattered wireless sensors is presented. Sensors within a cluster are expected to be communicating with a cluster head only. The cluster heads summarize and process sensor data from the clusters and maintain the link with the base station. The clustering is driven by the minimization of energy for all the sensors. Recent developments in clustering are used to support the work, and a cluster visualization interface is used to observe the simulation results.

73 citations

Journal ArticleDOI
TL;DR: Measurements of electric and magnetic fields emitted from Australian trams, trains and hybrid cars were investigated and results seem to be compatible with the evidence of the laboratory studies on the biological effects that are found in the literature, although they are far lower than international levels.
Abstract: Electricity is used substantially and sources of electric and magnetic fields are, unavoidably, everywhere. The transportation system is a source of these fields, to which a large proportion of the population is exposed. Hence, investigation of the effects of long-term exposure of the general public to low-frequency electromagnetic fields caused by the transportation system is critically important. In this study, measurements of electric and magnetic fields emitted from Australian trams, trains and hybrid cars were investigated. These measurements were carried out under different conditions, locations, and are summarised in this article. A few of the measured electric and magnetic field strengths were significantly lower than those found in prior studies. These results seem to be compatible with the evidence of the laboratory studies on the biological effects that are found in the literature, although they are far lower than international levels, such as those set up in the International Commission on Non-Ionising Radiation Protection guidelines.

61 citations


Cited by
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