Constructing living buildings: a review of relevant technologies for a novel application of biohybrid robotics

Biohybrid robotics takes an engineering approach to the expansion and exploitation of biological behaviours for application to automated tasks. Here, we identify the construction of living buildings and infrastructure as a high-potential application domain for biohybrid robotics, and review technological advances relevant to its future development. Construction, civil infrastructure maintenance and building occupancy in the last decades have comprised a major portion of economic production, energy consumption and carbon emissions. Integrating biological organisms into automated construction tasks and permanent building components therefore has high potential for impact. Live materials can provide several advantages over standard synthetic construction materials, including self-repair of damage, increase rather than degradation of structural performance over time, resilience to corrosive environments, support of biodiversity, and mitigation of urban heat islands. Here, we review relevant technologies, which are currently disparate. They span robotics, self-organizing systems, artificial life, construction automation, structural engineering, architecture, bioengineering, biomaterials, and molecular and cellular biology. In these disciplines, developments relevant to biohybrid construction and living buildings are in the early stages, and typically are not exchanged between disciplines. We, therefore, consider this review useful to the future development of biohybrid engineering for this highly interdisciplinary application.publishe

CrowdPower: A Novel Crowdsensing-as-a-Service Platform for Real-Time Incident Reporting

Crowdsensing using mobile phones is a novel addition to the Internet of Things applications suite. However, there are many challenges related to crowdsensing, including (1) the ability to manage a large number of mobile users with varying devices’ capabilities; (2) recruiting reliable users available in the location of interest at the right time; (3) handling various sensory data collected with different requirements and at different frequencies and scales; (4) brokering the relationship between data collectors and consumers in an efficient and scalable manner; and (5) automatically generating intelligence reports after processing the collected sensory data. No comprehensive end-to-end crowdsensing platform has been proposed despite a few attempts to address these challenges. In this work, we aim at filling this gap by proposing and describing the practical implementation of an end-to-end crowdsensing-as-a-service system dubbed CrowdPower. Our platform offers a standard interface for the management and brokerage of sensory data, enabling the transformation of raw sensory data into valuable smart city intelligence. Our solution includes a model for selecting participants for sensing campaigns based on the reliability and quality of sensors on users’ devices, then subsequently analysing the quality of the data provided using a clustering approach to predict user reputation and identify outliers. The platform also has an elaborate administration web portal developed to manage and visualize sensing activities. In addition to the architecture, design, and implementation of the backend platform capabilities, we also explain the creation of CrowdPower’s sensing mobile application that enables data collectors and consumers to participate in various sensing activities

Autopoietic-extended architecture: can buildings think?

To incorporate bioremedial functions into the performance of buildings and to balance generative architecture's dominant focus on computational programming and digital fabrication, this thesis first hybridizes theories of autopoiesis into extended cognition in order to research biological domains that include synthetic biology and biocomputation. Under the rubric of living technology I survey multidisciplinary fields to gather perspective for student design of bioremedial and/or metabolic components in generative architecture where generative not only denotes the use of computation but also includes biochemical, biomechanical, and metabolic functions. I trace computation and digital simulations back to Alan Turing's early 1950s Morphogenetic drawings, reaction-diffusion algorithms, and pioneering artificial intelligence (AI) in order to establish generative architecture's point of origin. I ask provocatively: Can buildings think? as a question echoing Turing's own "Can machines think?" Thereafter, I anticipate not only future bioperformative materials but also theories capable of underpinning strains of metabolic intelligences made possible via AI, synthetic biology, and living technology. I do not imply that metabolic architectural intelligence will be like human cognition. I suggest, rather, that new research and pedagogies involving the intelligence of bacteria, plants, synthetic biology, and algorithms define approaches that generative architecture should take in order to source new forms of autonomous life that will be deployable as corrective environmental interfaces. I call the research protocol autopoietic-extended design, theorizing it as an operating system (OS), a research methodology, and an app schematic for design studios and distance learning that makes use of in-field, e-, and m-learning technologies. A quest of this complexity requires scaffolding for coordinating theory-driven teaching with practice-oriented learning. Accordingly, I fuse Maturana and Varela's biological autopoiesis and its definitions of minimal biological life with Andy Clark's hypothesis of extended cognition and its cognition-to-environment linkages. I articulate a generative design strategy and student research method explained via architectural history interpreted from Louis Sullivan's 1924 pedagogical drawing system, Le Corbusier's Modernist pronouncements, and Greg Lynn's Animate Form. Thus, autopoietic-extended design organizes thinking about the generation of ideas for design prior to computational production and fabrication, necessitating a fresh relationship between nature/science/technology and design cognition. To systematize such a program requires the avoidance of simple binaries (mind/body, mind/nature) as well as the stationing of tool making, technology, and architecture within the ream of nature. Hence, I argue, in relation to extended phenotypes, plant-neurobiology, and recent genetic research: Consequently, autopoietic-extended design advances design protocols grounded in morphology, anatomy, cognition, biology, and technology in order to appropriate metabolic and intelligent properties for sensory/response duty in buildings. At m-learning levels smartphones, social media, and design apps source data from nature for students to mediate on-site research by extending 3D pedagogical reach into new university design programs. I intend the creation of a dialectical investigation of animal/human architecture and computational history augmented by theory relevant to current algorithmic design and fablab production. The autopoietic-extended design dialectic sets out ways to articulate opposition/differences outside the Cartesian either/or philosophy in order to prototype metabolic architecture, while dialectically maintaining: Buildings can think

Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application.

Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained

Location aware event driven multipath routing in Wireless Sensor Networks: Agent based approach

AbstractWireless Sensor Networks (WSNs) demand reliable and energy efficient paths for critical information delivery to sink node from an event occurrence node. Multipath routing facilitates reliable data delivery in case of critical information. This paper proposes an event triggered multipath routing in WSNs by employing a set of static and mobile agents. Every sensor node is assumed to know the location information of the sink node and itself. The proposed scheme works as follows: (1) Event node computes the arbitrary midpoint between an event node and the sink node by using location information. (2) Event node establishes a shortest path from itself to the sink node through the reference axis by using a mobile agent with the help of location information; the mobile agent collects the connectivity information and other parameters of all the nodes on the way and provides the information to the sink node. (3) Event node finds the arbitrary location of the special (middle) intermediate nodes (above/below reference axis) by using the midpoint location information given in step 1. (4) Mobile agent clones from the event node and the clones carry the event type and discover the path passing through special intermediate nodes; the path above/below reference axis looks like an arc. While migrating from one sensor node to another along the traversed path, each mobile agent gathers the node information (such as node id, location information, residual energy, available bandwidth, and neighbors connectivity) and delivers to the sink node. (5) The sink node constructs a partial topology, connecting event and sink node by using the connectivity information delivered by the mobile agents. Using the partial topology information, sink node finds the multipath and path weight factor by using link efficiency, energy ratio, and hop distance. (6) The sink node selects the number of paths among the available paths based upon the criticalness of an event, and (7) if the event is non-critical, then single path with highest path weight factor is selected, else multiple paths are selected for the reliable communication. The performance of the proposed scheme is tested in terms of performance parameters such as packet delivery ratio, energy consumption, latency, and overhead