Environmental Resilience Research Articles

Synchronized Resource Management: Integrating Waterand Power Systems for Environmental Resilience

Synchronized Resource Management: Integrating Waterand Power Systems for Environmental Resilience

Dynamic Modeling of Nonlinear Systems in Cyber-Physical Environments

Complex behavior understanding and prediction relies on dynamic modeling of nonlinear systems in cyber-physical contexts. Critical for improving control systems, anticipating maintenance needs, and bolstering resilience, it permits accurate portrayal of complex interactions between cyber and physical components. Guaranteeing efficient and adaptable performance in networked ecosystems is made possible by this insight. Dynamic modeling of nonlinear systems (DM-NS) in cyber-physical settings has a number of challenges, such as the need to accurately depict complex interdependencies, accommodate changes in real-time, and reduce uncertainty. Advanced modeling techniques are required to capture the subtle behaviours and maintain the accuracy of the models while trying to balance the complicated interactions between physical and cyber components. A novel strategy is suggested to tackle these obstacles: Analysing Nonlinear Systems Cyber-Physical Modeling (ANSC-PM). By integrating complex mathematical models with adaptive learning algorithms, ANSC-PM is able to characterize nonlinear system behaviours, taking into account the dynamic interplay between cyber and physical components. To remain relevant as system dynamics change, the suggested method adjusts in real-time. Numerous disciplines find ANSC-PM useful, such as control system optimization, robotic predictive maintenance, and networked environment resilience enhancement. The effectiveness of ANSC-PM is determined by careful simulation analysis, which provides insight into its possible benefits in improving system performance, flexibility, and resilience in complex cyber-physical settings. Developing a thorough and flexible strategy that is adapted to the intricacies of cyber-physical systems, this research makes a substantial contribution to the progress of dynamic modeling approaches.

STUDI POTENSI DAN PROBLEMATIKA DESA TERTINGGAL DI KABUPATEN KONAWE SELATAN

Analysis of all types of resources from the perspective of the Village Development Index (IDM), will clearly show all potential resources as strengths and as opportunities for future development. On the other hand, various life problems are also revealed as weaknesses and challenges that can be anticipated and must even be turned into opportunities for developing disadvantaged village communities. The research aims to describe the various potentials and at the same time the various problems contained in rural areas categorized as Disadvantaged Villages in South Konawe Regency. In this context, the resource potential within the scope of the Social Resilience Index, Economic Resilience and Environmental Resilience is studied from the perspective of the Regulation of the Minister of Villages, Development of Disadvantaged Regions and Transmigration of the Republic of Indonesia Number 2 of 2016 concerning the Developing Village Index. The research uses a qualitative approach which focuses on descriptive studies and phenomenological studies. All components of South Konawe society that are deemed worthy of providing information can be used as primary data sources. Primary data was carried out using participant observation, surveys, deep interviews and Focus Group Discussions. Analysis of the Village Development Index (IDM) through a process of weighting and ranking rural resource potential. The results of the research show that there is a rural area that is classified as a Very Disadvantaged Village (Pritama Village), because it is in the value range of less than 0.4907 and the existence of an area that is in the Disadvantaged Village category because it has a value of less than 0.599. Such conditions indicate vulnerability to natural disasters, economic shocks and social conflicts, so that villages experience difficulties in managing and utilizing the potential of their social, economic and ecological resources. The portrait of rural areas referred to as underdeveloped and very underdeveloped villages depicts the worst condition of resources according to the provisions of the 2016 Minister of Village Regulation, so that it appears very problematic in developing its existence towards developing villages, developed villages and up to independent villages. The existence of underdeveloped and very underdeveloped villages appears on the one hand to have sufficient resource potential to support the development of a rural area and develop the socio-economic welfare of its people. Although on the other hand, it was not able to achieve a score according to the provisions of the 2016 Minister of Village Regulation. In this context, for example, in the education dimension, high points were achieved, but the achievement in the social capital dimension appeared to be very low.

Diversifying natural resources for green recovery in China: Strategies and solutions

This study examines the importance of natural resource diversification for China’s green economic revival using the data from 1990 to 2021. The study makes use of a massive dataset spanning more than three decades, sheds light on the environmental sustainability and economic resilience measures taken by China’s resource business. As China’s economy grew at an unprecedented rate, environmental damage increased. Studies show increasing rates of carbon emissions, water use, and land deterioration. Information also indicates that people are becoming more conscious of the need for change and are open to adopting novel approaches and cutting-edge tools. The results of our study, which covers the years 1990 through 2021, on China’s efforts to diversify its natural resources for a green recovery highlight the importance of sustainable resource sector practices. China’s environmental problems, such as carbon emissions, water usage, and soil erosion, have worsened as the country’s economy has expanded rapidly. It’s not all bad, however. In an effort to reduce human use of natural resources, there has been a growth in the adoption of eco-friendly technologies and regulations. China is aware that it must find a middle ground between environmental conservation and economic growth. China needs to take advantage of these trends over time. The extraction of resources, the reduction of emissions, and the usage of land all need to be governed by clear and consistent standards. It’s crucial to put money into green technology like renewable energy and eco-efficient production. By taking the lead in ethical resource management, China can ensure a greener recovery for the world.

Adsorption Technologies for the Removal of Cytostatics in Water: A Review

One of the most common treatments for cancer disease requires the administration of cytostatics, which are very effective drugs in the elimination of cancerous cells, but are toxic for healthy tissues. After being administered to patients, they are excreted and frequently reach natural water bodies, due to their poor degradation in wastewater treatment plants (WWTPs), posing a global threat to the environment and human health. The study of proper treatment approaches for the effective removal of these hazardous drugs in WWTPs is thus a topic of concern and of utmost importance to ensure environmental integrity, resilience and sustainability. The aim of this work is to perform a comprehensive review of the application of adsorption-based processes for the treatment of aqueous matrices contaminated with cytostatics, which has never been addressed before. A detailed discussion on the operating conditions, type and concentrations of sorbents used, toxicity of the effluents and other relevant parameters is presented. This paper aims to help identify the most promising sorbents and conditions, the current knowledge gaps, and future challenges/perspectives on adsorption technologies (isolated or coupled with other processes) to tackle the problem of cytostatic fingerprints in water courses. Additionally, information concerning the implementation of these technologies from an environmental and economic (life cycle assessment) perspective is given.

Creating synergies between payments for ecosystem services, green bonds, and catastrophe insurance markets for enhanced environmental resilience

This study explores the potential of promoting sustainable land utilization practices through leveraging financial tools like green bonds, payment for ecosystem services (PES), and catastrophe insurance. In the proposed framework, a private manager issues green bonds to fund the replacement of degraded grasslands with forests, delivering the added advantages of replenishing stream water and protecting downstream hydropower plants from flooding. The downstream community engages in a PES agreement to enhance their water supply, while the hydropower plant secures flooding insurance from the manager, who utilizes green bond funding to cover potential damages following flooding. The study formulates a dynamic optimization model for the allocation of green bonds to support oak tree-led afforestation, ultimately bolstering the resilience of downstream communities and the power infrastructure. Results suggest that this green bond-based strategy holds promise for expeditious replacement of degraded grasslands with forests and can enhance ecosystem resilience by encouraging sustainable land use transformations. Furthermore, the research uncovers the potential for synergistic interactions between PES, green bonds, and catastrophe insurance markets. PES programs can also assist in repaying investments made through green bonds, while green bonds enable faster afforestation, leading to increased income from PES and improved resilience against flooding events.

Harnessing sulfate-reducing bacteria with plants growing to revitalize metal-tainted coal mine soils in Midwest China: metal sequestration performance, ecological networking interaction, and functional enzymatic prediction.

Heavy metal contamination from coal mining calls for advanced bioremediation, i.e., using sulfate-reducing bacteria (SRB) technology. Yet, the interaction of SRB with native soil microbiota during metal sequestration, especially in the presence of plants, remains ambiguous. In this study, we assessed the metal sequestration capabilities, ecological network interactions, and enzymatic functions in soils treated with a predominant SRB consortium, mainly Desulfovibrio (14 OTUs, 42.15%) and Desulfobulbus (7 OTUs, 42.27%), alongside Acacia dealbata (AD) and Pisum sativum (PS) plants. The SRB consortium notably enhanced the immobilization of metals such as Zn, Cu, As, and Pb in soil, with the conversion of metals to residual forms rising from 23.47 to 75.98%. Plant inclusion introduced variability, potentially due to changes in root exudates under metal stress. While AD flourished, PS demonstrated significant enhancement in conjunction with SRB, despite initial challenges. Comprehensive microbial analyses revealed the pivotal role of SRB in influencing microbial networking, underpinning critical ecological links. This interplay between plants and SRB not only enhanced microbial diversity but also enriched soil nutrients. Further, enzymatic assessments, highlighting enzymes like NADH:ubiquinone reductase and non-specific serine/threonine protein kinase, reinforced contribution of SRB to energy metabolism and environmental resilience of the entire soil microbial community. Overall, this research underscores the potential of SRB-driven bioremediation in revitalizing soils affected by coal mining.

Assessing potential impact of gut microbiome disruptions on the environmental stress resilience of indoor-reared Bombus terrestris.

Bumblebees are crucial for both natural ecosystems and agriculture, but their decline in distribution and abundance over the past decade is alarming. The global importance of bumblebees in natural ecosystems and agricultural food production cannot be overstated. However, the reported decline over the past decade has led to a surge of interest in understanding and addressing bumblebee population decline. Hence, we aimed to detect disruptions in the gut microbiome of male and worker bumblebees reared indoor and outdoor to assess potential resilience to environmental stress. Using the Illumina MiSeq platform for 16s rRNA amplicon sequencing, we analyzed the gut microbiome of male and worker bees that were raised indoors (designated as the IM and IW group) and those that were raised outdoors (also designated as the OM and OW group). Our results show presence of core bacteria Neisseriaceae, Orbaceae, Lactobacillaceae and Bifidobacteriaceae from indoor reared worker bees. However, a higher abundance of Bifidobacterium and absence of Fructobacillus from indoor reared worker bees was also observed. Indoor-reared male bees had lower diversity and fewer observed OTUs compared to outdoor-reared male bees. Additionally, the relative abundance of Actinobacteriota, Bacteroidota, and Firmicutes was significantly lower in indoor-reared males, while Proteobacteria was significantly increased. Despite this, we did not observe any dysbiosis in the gut microbiota of indoor-reared bumblebees when comparing the role of the gut symbionts among the groups. These results suggest that indoor-reared Bombus terrestris may be resilient to environmental stress when used as outdoor pollinators.

Sustainability and resilience against climate change provided by a territorial crop-livestock system

The development of territorial crop-livestock systems where exchanges between crops and livestock farms are managed in a synergistic way is seen as an opportunity to increase the sustainability and resilience of specialized agricultural systems against climatic disturbances. This study presents an innovative integrated assessment and modelling approach, based on the MAELIA platform, to assess the socio-economic and environmental sustainability and resilience of a territorial crop-livestock system. It is applied to a case study in the Vendée region (west France) where arable farms grow pulses to provide livestock farms with rich-protein feeds to achieve protein self-sufficiency, under two contrasting future climate pathways (RCP2.6 and RCP8.5) until 2050. Sustainability and resilience of this new organization are evaluated through 12 performances levels, including ecosystem services, and 3 criteria of dynamics for these 12 performances: variability, trend and resistance. Results show that the synergetic organization between farms can be sufficient to achieve protein self-sufficiency and to increase sustainability through the socio-economic performances of farmers and climate mitigation. Conversely, the degradation of some of the environmental performances points for a need to identify improved management practices. Regarding resilience, the new organization showed an overall increase in variability and degraded trends, while demonstrating greater resistance to shocks. We further discuss routes for the improvement of the MAELIA platform to help stakeholder identify the potential impacts and trade-offs of different scenarios in order to make informed decisions, minimize unintended consequences and increase resilience of agricultural systems.

54 Large-Scale Crispr Functional Characterization of Genomic Elements in Rainbow Trout (Oncorhynchus mykiss)

Abstract The wealth of genetic information that is now available for many agricultural animal species has opened vast potential to apply this new knowledge to improve agricultural production and sustainability. The field, however, is now faced with the daunting task of trying to understand what is arguably the most complex coded system known to mankind. In biomedical model systems, extensive efforts over decades have used single candidate gene approaches to uncover the function of many protein-coding genes and non-coding RNAs, but how this information translates to agricultural animals and their production traits is often unknown. Not only is repeating this vast effort for every agricultural species not practical, the current pace of genomic discovery is woefully inadequate for investigating animal genomes and therefore a radically new approach is needed. Using rainbow trout (RBT, Oncorhynchus mykiss) as a novel agricultural animal experimental system we have initiated a large-scale functional genomics screen that aims to characterize the function of over 1,000 genomic elements in a large animal model. The initial screen will focus on understanding how different genomic elements regulate growth and environmental resilience in these fish by combining multiplex CRISPR genome editing technology and phenotypic screening approaches to identify novel allele combinations from families of edited fish. The research is a paradigm shift in our approach to characterizing gene function, moving away from candidate-based approaches to a more genomics view of gene function. This work will shed light on the complex genetic mechanisms underlying two important production traits in fish while helping to advance our understanding of large animal functional genomics.

Distributed clean energy opportunities for US oil refinery operations

The oil and gas industry is increasingly seeking operational improvements to reduce costs and emissions while improving resilience. This study describes techno-economic analysis of opportunities for distributed energy resources that could be integrated to support oil and gas companies’ economic, environmental, and energy resiliency goals. Specifically, the analysis evaluates solar photovoltaics, wind turbines, battery energy storage, landfill gas, biomass, municipal solid waste-to-energy, solar steam for process heat, combined heat and power, and electrolyzers for hydrogen production at two hypothetical refineries, one located in Louisiana and the other in southern California. These technologies could reduce the sites’ consumption of grid electricity and/or natural gas and thus can help reduce emissions. This study employs the ReOPT tool and System Advisor Model to evaluate the techno-economic potential for clean energy technologies to support refineries in achieving energy goals, including energy cost savings, resiliency, and emissions reductions. Results indicate that the associated costs of emissions reductions via several distributed clean energy technologies are competitive with other emissions reduction strategies such as energy efficiency, reducing flaring, direct carbon capture and sequestration, and markets under certain conditions. There are also cost beneficial opportunities for the use of renewable energy for refining, especially for resilience, depending on local conditions such as resources and utility costs.

Towards a sustainable future: overcoming the challenges of post-war ecosystem reconstruction in Ukraine

The article explores the challenges of post-war ecosystem restoration in Ukraine and proposes pathways and strategies towards sustainable and resilient environmental recovery. It analyzes the risks associated with the clean-up and rehabilitation of hazardous substances, unexploded ordnance, and remnants of war, highlighting the potential ecological and human risks involved. Socio-economic risks related to environmental restoration are also examined, emphasizing the need to balance economic development with environmental protection. Additionally, the article addresses the management risks associated with ecosystem restoration, emphasizing the importance of effective governance and coordination among various stakeholders. Long-term challenges that Ukraine needs to address in its journey towards ecological restoration are identified, including resource constraints and institutional capacity building. Finally, the article outlines pathways and strategies for Ukraine to achieve sustainable and resilient post-war environmental recovery, emphasizing the importance of international cooperation, community engagement, and the integration of scientific research and innovative technologies. By addressing these challenges and adopting sustainable practices, Ukraine can pave the way for a future of ecological restoration, environmental resilience, and long-term sustainability.

Millets: Empowering the society with nutrient-rich superfoods to achieve sustainable development goals

Despite remarkable scientific progress in agriculture and medical sciences, the underlying causes of malnutrition and poverty remain stubborn challenges. This could be attributed to our limited comprehension on the intricate interplay of tradition, cultture, and the economy influence various facets of health. In the past, the sustainable practice of cultivating millets through natural and integrated farming, alongside mixed crop agriculture, played a vital role in maintaining a balanced lifestyle. Unfortunately, this valuable tradition has been neglected over time, partly due to various reasons and a lack of awareness. However, this presents an opportune moment to re-evaluate the potential of millets, not only for their health benefits but also for their positive impact on the environment and agricultural resilience. The Government of India (GoI) has taken steps in promoting millets through various programs and initiatives. Additionally, raising awareness through publications and validating traditional practices with scientific methods will not only facilitate research but also strengthen the bond between people, science, and their cultural heritage. Nonetheless, reintroducing millets into the Indian diet faces considerable challenges, primarily due to the pervasive influence of existing advertisements promoting cereal-based products, internal kitchen politics within households, market-driven agricultural practices, and economic factors. Despite these obstacles, the current manuscript aims to provide insights into developing a roadmap that enables the achievement of sustainable development goals through the integration of millets.

47 Exposure to Early Life Adversity is Related to Alterations in Neural Correlates of Inhibitory Control in Preadolescents: Findings from the ABCD Study Cohort

Objective:Rapid neurodevelopment occurs during adolescence, which may increase the developing brain’s susceptibility to environmental risk and resilience factors. Adverse childhood experiences (ACEs) may confer additional risk to the developing brain, where ACEs have been linked with alterations in BOLD signaling in brain regions underlying inhibitory control. Potential resiliency factors, like a positive family environment, may attenuate the risk associated with ACEs, but limited research has examined potential buffers to adversity’s impact on the developing brain. The current study aimed to examine how ACEs relate to BOLD response during successful inhibition on the Stop Signal Task (SST) in regions underlying inhibitory control from late childhood to early adolescence and will assess whether aspects of the family environment moderate this relationship.Participants and Methods:Participants (N= 9,080; Mage= 10.7, range= 9-13.8 years old; 48.5% female, 70.1% non-Hispanic White) were drawn from the larger Adolescent Brain Cognitive Development (ABCD) Study cohort. ACE risk scores were created (by EAS) using parent and child reports of youth’s exposure to adverse experiences collected at baseline to 2-year follow-up. For family environment, levels of family conflict were assessed based on youth reports on the Family Environment Scale at baseline and 2-year follow-up. The SST, a task-based fMRI paradigm, was used to measure inhibitory control (contrast: correct stop > correct go); the task was administered at baseline and 2-year follow-up. Participants were excluded if flagged for poor task performance. ROIs included left and right dorsolateral prefrontal cortex, anterior cingulate cortex, anterior insula, inferior frontal gyrus (IFG), and pre-supplementary motor area (pre-SMA). Separate linear mixed-effects models were conducted to assess the relationship between ACEs and BOLD signaling in ROIs while controlling for demographics (age, sex assigned at birth, race, ethnicity, household income, parental education), internalizing scores, and random effects of subject and MRI model.Results:Greater ACEs was associated with reduced BOLD response in the opercular region of the right IFG (b= -0.002, p= .02) and left (b= -0.002, p= .01) and right pre-SMA (b= -0.002, p= .01). Family conflict was related to altered activation patterns in the left pre-SMA, where youth with lower family conflict demonstrated a more robust negative relationship (b=.001, p= .04). ACEs were not a significant predictor in other ROIs, and the relationship between ACEs and BOLD response did not significantly differ across time. Follow-up brain-behavior correlations showed that in youth with lower ACEs, there was a negative correlation between increased activation in the pre-SMA and less impulsive behaviors.Conclusions:Preadolescents with ACE history show blunted activation in regions underlying inhibitory control, which may increase the risk for future poorer inhibitory control with downstream implications for behavioral/health outcomes. Further, results demonstrate preliminary evidence for the family environment’s contributions to brain health. Future work is needed to examine other resiliency factors that may modulate the impact of ACE exposure during childhood and adolescence. Further, clinical scientists should continue to examine the relationship between ACEs and neural and behavioral correlates of inhibitory control across adolescent development, as risk-taking behaviors progress.

Analyzing the Relationship Between Cultural Diversity, Social Capital, and Community Resilience in Jakarta, Indonesia

In Jakarta, Indonesia, this study explores the complex interrelationships among social capital, cultural diversity, and community resilience. Participants from a varied sample of 500 people, spanning a range of socioeconomic classes, and nationalities, shared their perspectives on social capital, cultural diversity, and community resilience. The results show a culturally diversified and affluent community where people feel they have strong social ties and are resilient. Indicators of community resilience, social capital, and cultural variety all show favorable connections according to statistical analysis. Regression analyses highlight the important roles that cultural variety, social capital that bonds, bridges, and links, and environmental, social, and economic resilience play in enhancing the overall resilience of Jakarta's communities. The sample's diversity in terms of demographics improves the findings' external validity. This research offers significant perspectives for practitioners and policymakers that aim to promote resilience in urban environments with various cultural backgrounds.

Genetic diversity assessment of a plant for forest restoration on the Korean Peninsula: A case study of Lespedeza cuneata G. Don (Fabaceae)

Given the challenges posed by climate change, ecological restoration is crucial for conserving biodiversity and improving environmental resilience. Ecological restoration aims to maintain and restore plant populations with high evolutionary capacity and facilitate beneficial genotype dispersion to adapt to environmental pressures. However, genetic diversity has been overlooked in restoration research. This study evaluated the genetic diversity of Lespedeza cuneata G. Don, a species targeted for restoration on the Korean Peninsula. Lespedeza cuneata is widely distributed in the Korean Peninsula and East Asia. However, this study confirmed that the heterozygosity of L. cuneata was relatively lower than that in studies of congeneric species. Analysis of the genetic structures on the peninsula revealed four clusters distinguished between several locations, and principal component analysis also identified clustering among four groups. Analysis of molecular variance results revealed that there was greater variation among (38.09%) than within (23.75%) populations, which is potentially due to the independent genotypes found in several of the populations. This study contributes to the understanding of genetic diversity within species targeted for restoration and provides valuable insights into the formulation of effective restoration plans integrating genetic aspects.

Climate change as challenges and prospects for architecture development

While the causes of climate changes remain poorly understood, their nature is undeniable. The shift in climate zone boundaries is accompanied by a rapid increase in the number and scale of extreme weather events, temperature and humidity variations. For many regions of Eurasia, climatic changes are manifested in the onset of desert and semi-desert (arid) climate zones. Extreme weather phenomena have a particularly threatening impact on urban life. For a variety of reasons, the urban environment is less resilient to weather disasters. The ways of increasing the resilience of urban environment, which are offered by the architectural mainstream, look insufficiently effective. The article substantiates the concept of using traditional and vernacular architectural and construction technologies preserved in regions with arid climate (Middle East, North Africa). Examples of successful application of traditional methods of house-building in combination with elements of the latest technologies are given.

Post-COVID-19's impact on green supply chain management and sustainable E-commerce performance: the moderating role of big data analytics.

This study investigates the relationship between COVID-19 and the adoption of green supply chain management practices (GSCM) in the Pakistani e-commerce industry. It also assesses the impact of these practices on ecological sustainability across three dimensions and explores the role of big data analytics (BDA) in enhancing them after the pandemic. The research utilized partial least squares structural equation modeling to evaluate data and test hypotheses. The research sample was composed of 390 managers operating within Pakistan's e-commerce industry. The study's preliminary findings reveal that COVID-19 has positively influenced the adoption of GSCM practices, which are moderated by BDA. Implementing GSCM has a positive impact on the perceived environmental and social resilience of e-commerce enterprises, but no significant effect on their perceived economic resilience. Additionally, GSCM acts as a mediator in the relationship between the impact of COVID-19 and the perceived environmental and social resilience of e-commerce firms, but not for economic resilience. This research focuses on Pakistan's e-commerce industry and investigates how COVID-19 affects the adoption of eco-friendly supply chain practices. It measures the impact of these practices on ecological sustainability using three dimensions. The study also examines how BDA can improve the adoption of GSCM in e-commerce, offering new insights into sustainability during and post-pandemic. The results recommend that the e-commerce industry can use BDA and GSCM practices to improve e-commerce sustainable performance. This is initial research that integrates COVID-19 impact, BDA, GSCM practices, and e-commerce sustainability in a single framework that was overlooked previously.

Strengthening Resilient Built Environments through Human Social Capital: A Path to Post-COVID-19 Recovery

There are strong indications that the built environment has had a great influence on the course of the COVID-19 pandemic and the post-disaster recovery. The COVID-19 pandemic has adversely affected both human and global development, while efforts to combat this menace call for an integrated human social capital index. This research seeks to enhance understanding of how the built environment can be enhanced through resilience against the backdrop of the COVID-19 pandemic. This study aims to investigate the impact of a resilient built environment on increasing resilience in the aftermath of the COVID-19 pandemic in Nigeria. The quantitative studies test the impact of four built environment resilience indices (built environment capital, disaster management indices, awareness of the COVID-19 pandemic, and built environment adaptive strategies) on human social capital and COVID-19 pandemic indices. This study reveals the role of human social capital in achieving a resilient built environment in the wake of the COVID-19 pandemic in Nigeria. Built environment capital, disaster management indices, and awareness of COVID-19 also indirectly affect the COVID-19 pandemic indices through human social capital. This study’s implications are useful for post-COVID-19 recovery, which is important for future planning of the built environment in Nigeria.

Comparative Analysis of Audio Processing Techniques on Doppler Radar Signature of Human Walking Motion Using CNN Models.

Artificial intelligence (AI) radar technology offers several advantages over other technologies, including low cost, privacy assurance, high accuracy, and environmental resilience. One challenge faced by AI radar technology is the high cost of equipment and the lack of radar datasets for deep-learning model training. Moreover, conventional radar signal processing methods have the obstacles of poor resolution or complex computation. Therefore, this paper discusses an innovative approach in the integration of radar technology and machine learning for effective surveillance systems that can surpass the aforementioned limitations. This approach is detailed into three steps: signal acquisition, signal processing, and feature-based classification. A hardware prototype of the signal acquisition circuitry was designed for a Continuous Wave (CW) K-24 GHz frequency band radar sensor. The collected radar motion data was categorized into non-human motion, human walking, and human walking without arm swing. Three signal processing techniques, namely short-time Fourier transform (STFT), mel spectrogram, and mel frequency cepstral coefficients (MFCCs), were employed. The latter two are typically used for audio processing, but in this study, they were proposed to obtain micro-Doppler spectrograms for all motion data. The obtained micro-Doppler spectrograms were then fed to a simplified 2D convolutional neural networks (CNNs) architecture for feature extraction and classification. Additionally, artificial neural networks (ANNs) and 1D CNN models were implemented for comparative analysis on various aspects. The experimental results demonstrated that the 2D CNN model trained on the MFCC feature outperformed the other two methods. The accuracy rate of the object classification models trained on micro-Doppler features was 97.93%, indicating the effectiveness of the proposed approach.