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Swarm planning for climate change

Swarm planning is a theory and practical approach to deal with uncertain futures. By anticipating scenarios such as a ‘post-carbon’ world and a ‘pre-adaptive’ landscape, it offers an alternative pathway to prepare for medium-term incremental and step changes. The focus is on the regional scale with a planning process to move from an unstable state (i.e. due to external impacts of climate change) towards a state of higher adaptive capacity. It increases the flexibility of spatial systems in two ways: assisting change in spatial land use over time; and catalysing the emergence of autonomous and more resilient developments. Swarm planning theory is used in two pilot designs and compared with regular planning processes. The results are presented in the form of new landscapes: the ‘Zero-Fossil Region’, where the design provides a spatial framework for a complete renewable energy supply, and the ‘Net Carbon Capture Landscape’, in which adaptation and mitigation strategies are designed to become carbon positive. The comparison illuminates the potential advantage of swarm planning to tackle climate change threats. La planification en essaims est une théorie et une approche pratique visant à traiter des avenirs incertains. Au moyen de scénarios prospectifs tels que celui d'un monde « post-carbone » et d'un paysage « préadaptatif », elle offre une voie alternative pour se préparer à des changements progressifs ou radicaux à moyen terme. L'accent est mis sur l’échelle régionale, avec un processus de planification permettant de passer d'un état instable (c'est-à-dire dû aux incidences extérieures du changement climatique) à un état présentant une plus grande capacité adaptative. Cela accroît de deux manières la flexibilité des systèmes spatiaux : en favorisant le changement dans l'utilisation spatiale des terrains au fil du temps; et en catalysant l’émergence de développements autonomes et plus résilients. La théorie de la planification en essaims est utilisée dans deux conceptions pilotes et comparée aux processus de planification habituels. Les résultats sont présentés sous la forme de nouveaux paysages : la « Région Zéro Energie Fossile », dans laquelle la conception fournit un cadre spatial permettant un approvisionnement énergétique entièrement renouvelable, et le « Paysage à Séquestration Nette de Carbone », dans lequel des stratégies d'adaptation et d'atténuation sont conçues pour assurer un bilan carbone positif. Cette comparaison se révèle éclairante quant à l'avantage potentiel de la planification en essaims pour s'attaquer aux menaces posées par le changement climatique. Mots clés: adaptation capacité adaptative cadre bâti résilience conception spatiale planification en essaims incertitude

Swarming landscapes

Robust reconstruction of sensor swarms floating through enclosed environments

A novel type of application for the exploration of enclosed or otherwise difficult to access environments requires large quantities of miniaturized sensor nodes to perform measurements while they traverse the environment in a “go with the flow” approach. Examples of these are the exploration of underground cavities and the inspection of industrial pipelines or mixing tanks, all of which have in common that the environments are difficult to access and do not allow position determination using e.g. GPS or similar techniques. The sensor nodes need to be scaled down towards the millimetre range in order to physically fit through the narrowest of parts in the environments and should measure distances between each other in order to enable the reconstruction of their positions relative to each other in offline analysis. Reaching those levels of miniaturization and enabling reconstruction functionality requires: 1) novel reconstruction algorithms that can deal with the specific measurement limitations and imperfections of millimetre-sized nodes, and 2) improved understanding of the relation between the highly constraint hardware design space of the sensor nodes and the reconstruction algorithms. To this end, this work provides a novel and highly robust sensor swarm reconstruction algorithm and studies the effect of hardware design trade-offs on its performance. Our findings based on extensive simulations, which push the reconstruction algorithm to its breaking point, provide important guidelines for the future development of millimetre-sized sensor nodes.

Mapping swarms of resource-limited sensor motes: Solely using distance measurements and non-unique identifiers

This work is on 3-D localization of sensor motes in massive swarms based solely on 1-D relative distance-measurements between neighbouring motes. We target applications in remote and difficult-to-access environments such as the exploration and mapping of the interior of oil reservoirs where hundreds or thousands of motes are used. These applications bring forward the need to use highly miniaturized sensor motes of less than 1 centimeter, thereby significantly limiting measurement and processing capabilities. These constraints, in combination with additional limitations posed by the environments, impede the communication of unique hardware identifiers, as well as communication with external, fixed beacons.

The Swarm

Sometimes religion and science are mentioned in one breath; both provide an explanatory framework for phenomena like uncertainty, chance or fate. In the meantime, science, or rather technology, has become a world religion. It’s a world religion, because technology connects: religion comes from the Latin “ Relegere” (literally re-assemble, connect).

Go-with-the-flow swarm sensing in inaccessible viscous media

This paper extends the 'go-with-the-flow' method to explore enclosed environments, like oil reservoirs, pipe lines that transport liquids, and industrial tanks for processing chemicals, where sensing nodes cannot establish communication with the external world. Nonetheless, large quantities of highly miniaturized, thus power-constrained sensor nodes are injected into these environment and flow through them along with the medium, monitoring their environment but also reconstructing their time-varying position from mutual communication, but without any communication to external base stations or beacons. The relative trajectories of nodes yield essential insights of the fluid flow in the otherwise inaccessible environment. We present a functional implementation of a ranging protocol accommodating size and energy constraints. Our simulation chain models node movement from different types of flow dynamics. It comprehensively assesses not only the performance of the communication and ranging protocols, but also of the reconstruction algorithm. Our assessments cover a wide range of different environments and flow profiles, including highly dynamic ones.