502 research outputs found
Internet of Things for Environmental Sustainability and Climate Change
Our world is vulnerable to climate change risks such as glacier retreat, rising temperatures, more variable and intense weather events (e.g., floods, droughts, and frosts), deteriorating mountain ecosystems, soil degradation, and increasing water scarcity. However, there are big gaps in our understanding of changes in regional climate and how these changes will impact human and natural systems, making it difficult to anticipate, plan, and adapt to the coming changes. The IoT paradigm in this area can enhance our understanding of regional climate by using technology solutions, while providing the dynamic climate elements based on integrated environmental sensing and communications that is necessary to support climate change impacts assessments in each of the related areas (e.g., environmental quality and monitoring, sustainable energy, agricultural systems, cultural preservation, and sustainable mining). In the IoT in Environmental Sustainability and Climate Change chapter, a framework for informed creation, interpretation and use of climate change projections and for continued innovations in climate and environmental science driven by key societal and economic stakeholders is presented. In addition, the IoT cyberinfrastructure to support the development of continued innovations in climate and environmental science is discussed
A Survey on Subsurface Signal Propagation
Wireless Underground Communication (WUC) is an emerging field that is being developed continuously. It provides secure mechanism of deploying nodes underground which shields them from any outside temperament or harsh weather conditions. This paper works towards introducing WUC and give a detail overview of WUC. It discusses system architecture of WUC along with the anatomy of the underground sensor motes deployed in WUC systems. It also compares Over-the-Air and Underground and highlights the major differences between the both type of channels. Since, UG communication is an evolving field, this paper also presents the evolution of the field along with the components and example UG wireless communication systems. Finally, the current research challenges of the system are presented for further improvement of the WUCs
Real-time In-situ Seismic Tomography in Sensor Network
Seismic tomography is a technique for illuminating the physical dynamics of the Earth by seismic waves generated by earthquakes or explosions. In both industry and academia, the seismic exploration does not yet have the capability of imaging seismic tomography in real-time and with high resolution. There are two reasons. First, at present raw seismic data are typically recorded on sensor nodes locally then are manually collected to central observatories for post processing, and this process may take months to complete. Second, high resolution tomography requires a large and dense sensor network, the real-time data retrieval from a network of large-amount wireless seismic nodes to a central server is virtually impossible due to the sheer data amount and resource limitations. This limits our ability to understand earthquake zone or volcano dynamics. To obtain the seismic tomography in real-time and high resolution, a new design of sensor network system for raw seismic data processing and distributed tomography computation is demanded. Based on these requirements, three research aspects are addressed in this work. First, a distributed multi-resolution evolving tomography computation algorithm is proposed to compute tomography in the network, while avoiding costly data collections and centralized computations. Second, InsightTomo, an end-to-end sensor network emulation platform, is designed to emulate the entire process from data recording to tomography image result delivery. Third, a sensor network testbed is presented to verify the related methods and design in real world. The design of the platform consists of hardware, sensing and data processing components
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or
"promising" concept for future cellular networks - in 2018 it became a reality.
Base stations (BSs) with 64 fully digital transceiver chains were commercially
deployed in several countries, the key ingredients of Massive MIMO have made it
into the 5G standard, the signal processing methods required to achieve
unprecedented spectral efficiency have been developed, and the limitation due
to pilot contamination has been resolved. Even the development of fully digital
Massive MIMO arrays for mmWave frequencies - once viewed prohibitively
complicated and costly - is well underway. In a few years, Massive MIMO with
fully digital transceivers will be a mainstream feature at both sub-6 GHz and
mmWave frequencies. In this paper, we explain how the first chapter of the
Massive MIMO research saga has come to an end, while the story has just begun.
The coming wide-scale deployment of BSs with massive antenna arrays opens the
door to a brand new world where spatial processing capabilities are
omnipresent. In addition to mobile broadband services, the antennas can be used
for other communication applications, such as low-power machine-type or
ultra-reliable communications, as well as non-communication applications such
as radar, sensing and positioning. We outline five new Massive MIMO related
research directions: Extremely large aperture arrays, Holographic Massive MIMO,
Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive
MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin
Decentralized Convex Optimization for Wireless Sensor Networks
Many real-world applications arising in domains such as large-scale machine learning, wired and wireless networks can be formulated as distributed linear least-squares over a large network. These problems often have their data naturally distributed. For instance applications such as seismic imaging, smart grid have the sensors geographically distributed and the current algorithms to analyze these data rely on centralized approach. The data is either gathered manually, or relayed by expensive broadband stations, and then processed at a base station. This approach is time-consuming (weeks to months) and hazardous as the task involves manual data gathering in extreme conditions. To obtain the solution in real-time, we require decentralized algorithms that do not rely on a fusion center, cluster heads, or multi-hop communication. In this thesis, we propose several decentralized least squares optimization algorithm that are suitable for performing real-time seismic imaging in a sensor network. The algorithms are evaluated and tested using both synthetic and real-data traces. The results validate that our distributed algorithm is able to obtain a satisfactory image similar to centralized computation under constraints of network resources, while distributing the computational burden to sensor nodes
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
Signals in the Soil: An Introduction to Wireless Underground Communications
In this chapter, wireless underground (UG) communications are introduced. A detailed overview of WUC is given. A comprehensive review of research challenges in WUC is presented. The evolution of underground wireless is also discussed. Moreover, different component of UG communications is wireless. The WUC system architecture is explained with a detailed discussion of the anatomy of an underground mote. The examples of UG wireless communication systems are explored. Furthermore, the differences of UG wireless and over-the-air wireless are debated. Different types of wireless underground channel (e.g., In-Soil, Soil-to-Air, and Air-to-Soil) are reported as well
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