Biomimicry and nature-inspired solutions for environmental sustainability
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Rajesh Sisodia
Abstract
Biomimicry, from the Greek words for “life” (bio) and “imime” (-mimesis), is an emerging field that aims to extrapolate the systems and structures found in nature to be used in a variety of man-made contexts. Biomimicry is the process of finding solutions to human issues by modeling human creations after solutions found in nature. But in environmental communication, we talk about how to use words to fix the planet’s problems. In the domain of biomimicry, the term “mirroring” is used to describe the mimesis of communication. Objective: The purpose of this research is to gain a better understanding of the relationship between biomimicry and the process of communicating with the environment regarding anthropogenic causes. The research has a qualitative, social-scientific stance; it serves as a model for a case study on active apps that focus on proenvironmental behavioral goals. The study was conducted using a multidisciplinary approach, and the results zeroed in on the domains most profoundly impacted by biomimicry’s use in environmental discourse. Findings: The outcomes of the study indicate an Indian-based program called hejje (meaning pug mark) that was introduced in Bandipur Tiger Reserve that simulates tigers’ territorial route migratory patterns to provide a potential trajectory path. In order to anticipate poaching activity within Bandipur Tiger Reserve, researchers have developed a trajectory path that is a simulation of the historical route used by tigers to establish their territories there. Conclusion: This case study suggests that biomimicry can be used as a means of resolving anthropogenic environmental challenges by employing technology that percolates from biomimicking.
Abstract
Biomimicry, from the Greek words for “life” (bio) and “imime” (-mimesis), is an emerging field that aims to extrapolate the systems and structures found in nature to be used in a variety of man-made contexts. Biomimicry is the process of finding solutions to human issues by modeling human creations after solutions found in nature. But in environmental communication, we talk about how to use words to fix the planet’s problems. In the domain of biomimicry, the term “mirroring” is used to describe the mimesis of communication. Objective: The purpose of this research is to gain a better understanding of the relationship between biomimicry and the process of communicating with the environment regarding anthropogenic causes. The research has a qualitative, social-scientific stance; it serves as a model for a case study on active apps that focus on proenvironmental behavioral goals. The study was conducted using a multidisciplinary approach, and the results zeroed in on the domains most profoundly impacted by biomimicry’s use in environmental discourse. Findings: The outcomes of the study indicate an Indian-based program called hejje (meaning pug mark) that was introduced in Bandipur Tiger Reserve that simulates tigers’ territorial route migratory patterns to provide a potential trajectory path. In order to anticipate poaching activity within Bandipur Tiger Reserve, researchers have developed a trajectory path that is a simulation of the historical route used by tigers to establish their territories there. Conclusion: This case study suggests that biomimicry can be used as a means of resolving anthropogenic environmental challenges by employing technology that percolates from biomimicking.
Chapters in this book
- Frontmatter I
- Contents V
- Contributing authors IX
- Synchronizing neural networks, machine learning for medical diagnosis, and patient representation: looping advanced optimization strategies assisting experts for complex mechanisms behind health and disease detection 1
- The future of predictive health: evaluating the role of neural network based hybrid models in healthcare 19
- An overview of new trends on deep learning models for diabetes risk prediction 47
- A study on the detection and diagnosis of cervical cancer using machine and deep learning models 57
- Sentiments and opinions shared on social media during the COVID-19 pandemic using machine learning techniques 71
- Combining decision tree and Bayesian networks for improved predictive analytics 91
- Emerging trends in hybrid information systems modeling in artificial intelligence 115
- Hybrid approaches for improving cybersecurity and network intrusion system 153
- IoT security enhancement through blockchain solutions 167
- Securing cloud data exchange related to IoT devices: key challenges and its machine learning solutions 177
- Hybrid information systems for modeling traffic management and control 201
- Integrative hybrid information systems for enhanced traffic maintenance and control in Bangalore: a synchronized approach 223
- A comprehensive study for weapon detection technologies for surveillance under different YoloV8 models on primary data 241
- Strategic design of asymmetric graphene and ReS2 field-effect transistors using nonlinear optimization and machine learning 269
- Recent advancements in perfect difference networks for image recognition: a survey and analysis 307
- Image to text to speech: a web-based application using optical character recognition and speech synthesis 329
- Biomimicry and nature-inspired solutions for environmental sustainability 343
- Intelligent analysis of flowers and knowledge generation: an empirical study for agriculture 4.0 355
- Harnessing the power of hybrid models for supply chain management and optimization 407
- Optimizing long short-term memory networks for univariate time series forecasting: a comprehensive guide 427
- Optimizing bidirectional long short-term memory networks for univariate time series forecasting: a comprehensive guide 443
- Optimizing convolutional neural networks for univariate time series forecasting: a comprehensive guide 459
- Optimizing gated recurrent unit networks for univariate time series forecasting: a comprehensive guide 473
- Artificial intelligence-based diagnosis and treatment of childhood bronchial allergies 491
- Index 501
Chapters in this book
- Frontmatter I
- Contents V
- Contributing authors IX
- Synchronizing neural networks, machine learning for medical diagnosis, and patient representation: looping advanced optimization strategies assisting experts for complex mechanisms behind health and disease detection 1
- The future of predictive health: evaluating the role of neural network based hybrid models in healthcare 19
- An overview of new trends on deep learning models for diabetes risk prediction 47
- A study on the detection and diagnosis of cervical cancer using machine and deep learning models 57
- Sentiments and opinions shared on social media during the COVID-19 pandemic using machine learning techniques 71
- Combining decision tree and Bayesian networks for improved predictive analytics 91
- Emerging trends in hybrid information systems modeling in artificial intelligence 115
- Hybrid approaches for improving cybersecurity and network intrusion system 153
- IoT security enhancement through blockchain solutions 167
- Securing cloud data exchange related to IoT devices: key challenges and its machine learning solutions 177
- Hybrid information systems for modeling traffic management and control 201
- Integrative hybrid information systems for enhanced traffic maintenance and control in Bangalore: a synchronized approach 223
- A comprehensive study for weapon detection technologies for surveillance under different YoloV8 models on primary data 241
- Strategic design of asymmetric graphene and ReS2 field-effect transistors using nonlinear optimization and machine learning 269
- Recent advancements in perfect difference networks for image recognition: a survey and analysis 307
- Image to text to speech: a web-based application using optical character recognition and speech synthesis 329
- Biomimicry and nature-inspired solutions for environmental sustainability 343
- Intelligent analysis of flowers and knowledge generation: an empirical study for agriculture 4.0 355
- Harnessing the power of hybrid models for supply chain management and optimization 407
- Optimizing long short-term memory networks for univariate time series forecasting: a comprehensive guide 427
- Optimizing bidirectional long short-term memory networks for univariate time series forecasting: a comprehensive guide 443
- Optimizing convolutional neural networks for univariate time series forecasting: a comprehensive guide 459
- Optimizing gated recurrent unit networks for univariate time series forecasting: a comprehensive guide 473
- Artificial intelligence-based diagnosis and treatment of childhood bronchial allergies 491
- Index 501
