infrastructure monitoring
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Cities must address many challenges including air quality, climate change and the health and wellbeing of communities. Public authorities and developers increasingly look to improve these through the implementation of interventions and innovations, such as low traffic neighbourhoods, deep housing retrofits and green infrastructure. Monitoring the impacts of interventions is essential to determine the success of such projects and to build evidence for broader urban transformation. In this paper we present a mixed-method cross-disciplinary approach that brings together cutting edge atmospheric and data science, measurements of activity in public spaces and novel methods to assess wellbeing-promoting behaviours. The Manchester Urban Observatory focuses on living areas that have a high density of inter-related systems, which require observation, understanding and intervention at multiple levels. This must be completed in line with urban planning goals as well as a clear and succinct data solution that allows robust scientific conclusions to be made and viewed in real time. Delivery of such a monitoring strategy is not trivial and is time, resource and expertise heavy. This paper discusses the methods employed by the Manchester Urban Observatory to monitor the effectiveness off interventions implemented within cities and effective communication strategies with local communities.

Wireless sensor networks (WSNs) especially with sensor nodes communicating with each other in medium other than air have been naive area of research since the last few years. In comparison to underwater communication, wireless underground sensor networks (WUSNs) are now being used in a large number of applications ranging from environmental observation, estimating chances of earthquake, communicating in underground tunnels or mines, and infrastructure monitoring to soil monitoring for agricultural purposes. In spite of all such promising applications, due to harsh and dynamically changing soil characteristics including soil type, water content in soil, and soil temperature, underground communication with conventional electromagnetic (EM) wave-based technology could not prove to be feasible for long-distance communication. Alternatively, due to magnetic permeability of soil being similar to air, magnetic induction- (MI-) based approach was adopted using magnetic coils as antenna for sensor nodes. Subsequently, MI waveguide and 3D coil mechanisms were considered to improve the system efficiency. Attributing to different characteristics of underlying transmission channels, communication protocols as well as architecture of MI-based WUSNS (MI-WUSNs) have been developed with different approaches. In this review paper, in addition to the latest advancements made for MI-WUSNs, closely associated areas of MI-WUSNs have also been explored. Additionally, research areas which are still open to be worked upon have been detailed out.

Cohort analysis is a new practical method for e-commerce customers’ research, trends in their behavior, and experience during the COVID-19 crisis. The purpose of the research is to validate the efficiency of this method on the e-commerce records data set and find out the critical factors associated with customer awareness and loyalty levels. The cohort analysis features engineering, descriptive statistics, and exploratory data analysis are the main methods used to reach the study purpose. The research results showed that cohort analysis could answer various business questions and successfully solve real-world problems in e-commerce customer research. It could be extended to analyze user satisfaction with a platform’s technical performance and used for infrastructure monitoring. Obtained insights on e-commerce customers’ awareness and loyalty levels show the likeliness of a user to make a purchase or interact with the platform. Key e-business aspects from a customer point of view are analyzed and augment the user-experience understanding to strengthen customers’ relationships in e-commerce.

Worldwide, transport infrastructure is increasingly vulnerable to ageing-induced deterioration and climate-related hazards. Oftentimes inspection and maintenance costs far exceed available resources, and numerous assets lack any rigorous structural evaluation. Space-borne Synthetic Aperture Radar Interferometry (InSAR) is a powerful remote-sensing technology, which can provide cheaper deformation measurements for bridges and other transport infrastructure with short revisit times, while scaling from the local to the global scale. As recent studies have shown the InSAR accuracy to be comparable with traditional monitoring instruments, InSAR could offer a cost-effective tool for long-term, near-continuous deformation monitoring, with the possibility to support inspection planning and maintenance prioritisation, while maximising functionality and increasing the resilience of infrastructure networks. However, despite the high potential of InSAR for structural monitoring, some important limitations need to be considered when applying it in reality. This paper identifies and discusses the challenges of using InSAR for the purpose of structural monitoring, with a specific focus on bridges and transport networks. Examples are presented to illustrate current practical limitations of InSAR; possible solutions and promising research directions are identified. The aim of this study is to motivate future action in this area and highlight the InSAR advances needed to overcome current challenges.

<p>Serangan pada jaringan saat ini sangat sering terjadi, dengan semakin banyaknya cara untuk melakukan pengaksesan terhadap data dan semakin berkembangnya teknologi yang digunakan tentunya akan menyebabkan meningkatnya ancaman keamanan suatu jaringan. Evaluasi manajemen keamanan informasi menggunakan indeks keamanan informasi (KAMI) yang dilakukan pada jaringan di UIN Sunan Kalijaga Yogyakarta didapatkan hasil indeks 407, yang dianggap masih belum optimal. Hal ini yang mendasari perlunya implementasi Open Source SIEM (OSSIM) ke dalam indeks KAMI. Penelitian ini dilakukan untuk mengoptimalkan proses keamanan informasi agar dapat bekerja sesuai dengan standar indeks KAMI. Metode penelitian yang digunakan meliputi studi literatur, melakukan Pre-Assesment Indeks KAMI, mengimplementasi infrastruktur OSSIM, monitoring indeks keamanan informasi menggunakan teknologi OSSIM, dan melakukan Post-Assesment Indeks KAMI, tahapan akhir ini menganalisis hasil monitoring untuk dibuat perbandingan bagaimana kondisi jaringan sebelum dan sesudah diimplementasikan OSSIM pada jaringan. Skor nilai perbandingan dari hasil penelitian terkait Indeks KAMI menunjukkan peningkatan skor penilaian sebesar 25, setelah diterapkan penggunaan OSSIM dari sebelumnya tanpa penerapan OSSIM sebesar nilai 407 menjadi 432. Peningkatan indeks KAMI membantu menaikan nilai pada aspek tata kelola, pengelolaan asset dan teknologi, namun tingkat kelayakan keamanan informasi masih di level I+ sampai dengan II+ sehingga keamanan informasi pada jaringan tidak layak dan butuh perbaikan.</p><p> </p><p><em><strong>Abstract</strong></em></p><p><em>Attacks on networks today are very common, with more and more ways to access data and the development of technology used, they will certainly cause an increase in network security threats. Evaluation of information security management using the information security index (KAMI) conducted on the network at UIN Sunan Kalijaga Yogyakarta obtained an index result of 407, which is considered still not optimal. This underlies the need to implement Open Source SIEM (OSSIM) into the KAMI index. This research was conducted to optimize the information security process so that it can work according to the KAMI index standards. The research methods used include literature study, conducting KAMI Index Pre-Assessment, implementing OSSIM infrastructure, monitoring information security index using OSSIM technology and conducting KAMI Index Post-Assessment, this final stage analyzes the results of monitoring to make comparisons of network conditions before and after implementation of OSSIM on the network. Comparative scores from the results of research related to the KAMI Index show an increase in the score of 25, after applying OSSIM from before without applying OSSIM, the value of 407 becomes 432. The increase in the KAMI index helps raise the value of governance aspects, asset management and technology, but the level of information security eligibility is still at the level of I+ to II+ so the information security on the network is not feasible and needs improvement.</em></p><p><em> </em></p><p><em><strong><br /></strong></em></p>

Covid-19 has spread to several countries including Indonesia. Responding to the growing trend of the spread and transmission of Covid-19 which continues to increase, it is necessary to identify, overcome, and prevent it through the implementation of Occupational safety and health (K3). This study uses a descriptive research method with a case study approach. Implementation in health facilities is still not optimal, as seen from the increasing number of affected health workers. In this study, the authors wanted to see indicators of officer compliance in implementing K3, supporting facilities and infrastructure, monitoring and evaluation from the Bogor District Health Office. The importance of implementing K3 in health facilities for health workers as the front line of health services dealing with Covid-19. This is indicated by the number of health workers affected by Covid-19. Implementation of K3 in health facilities to reduce the number of health workers

Abstract The use of modern information and communication technologies is an essential condition for the formation of the transport infrastructure of a smart city. Scientific and methodological approaches are developed to effectively monitor the transport infrastructure of a smart city based on multi-channel metric learning in the Internet of Things. The proposed solutions provide invariance to the type and nature of the movement of objects. The principles of technical implementation of the proposed method are substantiated using the characteristics of unmanned aerial vehicles of a smart city. Adaptive automatic switching of transport infrastructure monitoring channels is implemented in the form of a neural network analyzer software.