Humankind is now in an age wherein generations of humans have never lived without ubiquitous computing and the internet. This 'AI / IoT generation is creative, innovative and adaptable; however, the relentlessness, complexity, and volume of technological, biotechnological, healthcare, social, cultural, and emotional changes and stressors cause humans many personal, social, and environmental traumas. This book presents a vision for designing and managing the complexity and multidimensionality of the world's emerging technological and ai/robotics-enabled environments that is grounded in current methods for designing human-centred, complex, interactive systems.
This book discusses the coexistence and coevolution of humans and intelligent, adaptive environments during a transformational age during which society is confronting social, environmental, and health crises. Defining the creative strategies needed as 'heroes' of the near future, this book investigates the coexistence/coevolution concept that entails how humans should co-evolve with their 'smart artifact ecologies' by designing dynamic environments that ameliorate technology-induced trauma. In understanding the emerging AI-enabled, Non-Humanoid Social Robotics (NH-SR) and IoT-enabled environments, the reader will develop an understanding of how to design environments for future generations.
Coexistence and Coevolution of Humans and Intelligent, Adaptive Environments is a thoughtful read for graduate students, researchers and academics interested in Architecture, Systems Engineering; Computational/Robotic/Intelligent Architecture; Human Factor Engineering; Robotic Engineering; Mechatronics Engineering; Human-Systems Integration; and Human-AI-Robot Teaming. It equally speaks to social scientists, humanists, futurists, and visionary architects whose work navigates the evolving entanglements of technology, humanity, and design.
Tarek H. Mokhtar, Associate AIA, Ph.D., M.Sc., is a prominent scholar whose interdisciplinary research integrates architectural robotics, information technology, artificial intelligence, and non-humanoid social robotics. With over twenty-five years of distinguished academic and practical contributions, Dr. Mokhtar holds U.S. patents in spatial intelligence systems and dynamic robotic environments. At Alfaisal University, Saudi Arabia, he directs the DIMENSIONS Startup Studios, INVENT Center for Innovation and Design Thinking, and the DaVinciAT Research Center, overseeing its specialized labs (Morph, Edge, RoboTek, and iDNA), dedicated to advanced technologies in cyber-physical systems and robotics. Demonstrating his exceptional ability to garner support for groundbreaking research, he secured a significant $1 million grant to fund DaVinciAT's innovative initiatives. His scholarly impact in non-humanoid social robotics is widely recognized through numerous publications and international conference leadership roles. Dr. Mokhtar holds a Ph.D. in Planning, Design, and the Built Environment, specializing in Architectural Robotics, from Clemson University, USA.
Joe Manganelli, AIA, CHFP, LEED AP BD+C, PhD, is a practicing registered architect and board-certified human factors professional, as well as a sustainable design specialist. His goal is improving the capacity of the built environment to enhance human cognitive and physical health, well-being, and performance. For more than twenty years, Dr Manganelli's research and practice integrates constructs and methods from architecture, human factors, systems engineering, cognitive science, evolutionary biology, and sustainability. His architectural practice has focused on advanced industrial facilities design and his human factors practice has focused on industrial, healthcare, and automotive concerns. This background, which was developed to learn how to better design for humans, especially in task-oriented, mission-critical environments, has led more recently to research opportunities developing constructs and methods for human-centered cyber-physical systems, as well as methods for measuring system of systems performance of human-AI-robot teams.
