The impact of agricultural activities on water quality: a case for collaborative catchment-scale management using integrated wireless sensor networks

The challenge of improving water quality is a growing global concern, typified by the European Commission Water Framework Directive and the United States Clean Water Act. The main drivers of poor water quality are economics, poor water management, agricultural practices and urban development. This paper reviews the extensive role of non-point sources, in particular the outdated agricultural practices, with respect to nutrient and contaminant contributions. Water quality monitoring (WQM) is currently undertaken through a number of data acquisition methods from grab sampling to satellite based remote sensing of water bodies. Based on the surveyed sampling methods and their numerous limitations, it is proposed that wireless sensor networks (WSNs), despite their own limitations, are still very attractive and effective for real-time spatio-temporal data collection for WQM applications. WSNs have been employed for WQM of surface and ground water and catchments, and have been fundamental in advancing the knowledge of contaminants trends through their high resolution observations. However, these applications have yet to explore the implementation and impact of this technology for management and control decisions, to minimize and prevent individual stakeholder’s contributions, in an autonomous and dynamic manner. Here, the potential of WSN-controlled agricultural activities and different environmental compartments for integrated water quality management is presented and limitations of WSN in agriculture and WQM are identified. Finally, a case for collaborative networks at catchment scale is proposed for enabling cooperation among individually networked activities/stakeholders (farming activities, water bodies) for integrated water quality monitoring, control and management

Wireless Sensor Networks for Oceanographic Monitoring: A Systematic Review

Monitoring of the marine environment has come to be a field of scientific interest in the last ten years. The instruments used in this work have ranged from small-scale sensor networks to complex observation systems. Among small-scale networks, Wireless Sensor Networks (WSNs) are a highly attractive solution in that they are easy to deploy, operate and dismantle and are relatively inexpensive. The aim of this paper is to identify, appraise, select and synthesize all high quality research evidence relevant to the use of WSNs in oceanographic monitoring. The literature is systematically reviewed to offer an overview of the present state of this field of study and identify the principal resources that have been used to implement networks of this kind. Finally, this article details the challenges and difficulties that have to be overcome if these networks are to be successfully deployed

Reliable Lifespan Evaluation of a Remote Environment Monitoring System Based on Wireless Sensor Networks and Global System for Mobile Communications

The use of wireless sensor networks (WSN) for monitoring physical and chemical variables in large areas allows density and frequency measurements which have been unavailable to date in classical measurement systems. To fully take advantage of this technology in a particular application, besides an accurate design and selection of all the components involved in its operation, it is essential to dispose of reliable lifetime estimation prior to deployment. This paper presents an experimental approach to determine the actual lifetime of such battery-operated systems, making use of a custom WSN architecture, and for different batteries technologies. To render a reliable evaluation, the energy consumption of the sensor nodes under their different operation modes, in correlation with the battery characteristics and the voltage regulation system, is jointly considered. The result is a complete and practical lifetime model, whose appropriate performance has been validated in a real deployment scenario

Energy harvesting and wireless transfer in sensor network applications: Concepts and experiences

Advances in micro-electronics and miniaturized mechanical systems are redefining the scope and extent of the energy constraints found in battery-operated wireless sensor networks (WSNs). On one hand, ambient energy harvesting may prolong the systems lifetime or possibly enable perpetual operation. On the other hand, wireless energy transfer allows systems to decouple the energy sources from the sensing locations, enabling deployments previously unfeasible. As a result of applying these technologies to WSNs, the assumption of a finite energy budget is replaced with that of potentially infinite, yet intermittent, energy supply, profoundly impacting the design, implementation, and operation of WSNs. This article discusses these aspects by surveying paradigmatic examples of existing solutions in both fields and by reporting on real-world experiences found in the literature. The discussion is instrumental in providing a foundation for selecting the most appropriate energy harvesting or wireless transfer technology based on the application at hand. We conclude by outlining research directions originating from the fundamental change of perspective that energy harvesting and wireless transfer bring about

Keberkesanan program simulasi penapis sambutan dedenyut terhingga (FIR) terhadap kefahaman pelajar kejuruteraan elektrik

Kefahaman merupakan aset bagi setiap pelajar. Ini kerana melalui kefahaman pelajar dapat mengaplikasikan konsep yang dipelajari di dalam dan di luar kelas. Kajian ini dijalankan bertujuan menilai keberkesanan program simulasi penapis sambutan dedenyut terhingga (FIR) terhadap kefahaman pelajar kejuruteraan elektrik FKEE, UTHM dalam mata pelajaran Pemprosesan Isyarat Digital (DSP) bagi topik penapis FIR. Metodologi kajian ini berbentuk kaedah reka bentuk kuasi�eksperimental ujian pra-pasca bagi kumpulan-kumpulan tidak seimbang. Seramai 40 responden kajian telah dipilih dan dibahagi secara rawak kepada dua kllmpulan iaitu kumpulan rawatan yang menggunakan program simulasi penapis FIR dan kumpulan kawalan yang menggunakan kaedah pembelajaran berorientasikan modul pembelajaran DSP UTHM. Setiap responden menduduki dua ujian pencapaian iaitu ujian pra dan ujian pasca yang berbentuk kuiz. Analisis data berbentuk deskriptif dan inferens dilakllkan dengan menggunakan Peri sian Statistical Package for Social Science (SPSS) versi 11.0. Dapatan kajian menunjukkan kedua-dua kumpulan pelajar telah mengalami peningkatan dari segi kefahaman iaitu daripada tahap tidak memuaskan kepada tahap kepujian selepas menggunakan kaedah pembelajaran yang telah ditetapkan bagi kumpulan masing-masing. Walaubagaimanapun, pelajar kumpulan rawatan menunjukkan peningkatan yang lebih tinggi sedikit berbanding pelajar kumpulan kawalan. Namun begitu, dapatan kajian secara ujian statistik menunjukkan tidak terdapat perbezaan yang signifikan dari segi pencapaian markah ujian pasca di antara pelajar kumpulan rawatan dengan pelajar kumpulan kawalan. Sungguhpun begitu, penggunaan program simulasi penapis FIR telah membantu dalam peningkatan kefahaman pelajar mengenai topik penapis FIR

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Unmanned Aerial System-Based Data Ferrying over a Sensor Node Station Network in Maize

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Underground Mining Monitoring and Communication Systems based on ZigBee and GIS

ZigBee as a wireless sensor network (WSN) was developed for underground mine monitoring and communication systems. The radio wave attenuations between ZigBee nodes were investigated to measure underground communication distances. Various sensor node arrangements of ZigBee topologies were evaluated. A system integration of a WSN-assisted GIS for underground mining monitoring and communication from a surface office was proposed. The controllable and uncontrollable parameters of underground environments were assessed to establish a reliable ZigBee network