1536-1268/02/$17.00 © 2002 IEEEPERVASIVEcomputing59REACHING WEISER’S VISIONConnecting the PhysicalWorld with PervasiveNetworksMark Weiser envisioned a worldin which computing is so per-vasive that everyday devices cansense their relationship to usand to each other. They could,thereby, respond so appropriately to our actions thatthe computing aspects would fade into the back-ground. Underlying this vision is the assumptionthat sensing a broad set of phys-ical phenomena, rather than justdata input, will become a com-mon aspect of small, embeddedcomputers and that these deviceswill communicate with eachother (as well as to some morepowerful infrastructure) to orga-nize and coordinate their actions. Recall the story of Sal inWeiser’s article; Sal looked out her window and saw“tracks” as evidence of her neighbors’ morningstrolls. What sort of system did this seemingly sim-ple functionality imply? Certainly Weiser did notenvision ubiquitous cameras placed throughout theneighborhood. Such a solution would be far tooheavy for the application’s relatively casual natureas well as quite invasive with respect to personal pri-vacy. Instead, Weiser posited the existence of far lessintrusive instrumentation in neighborhood spaces—perhaps smart paving stones that could detect localactivity and indicate the walker’s direction based onexchanges between neighboring nodes. As we havemarched technology forward, we are now in a posi-tion to translate this aspect of Weiser’s vision to real-ity and apply it to a wide range of important appli-cations, both computing and social. Other articles in this issue address the user inter-face-, application-, software-, and device-level designchallenges associated with realizing Weiser’s vision.Here, we address the challenges and opportunitiesof instrumenting the physical world with pervasivenetworks of sensor-rich, embedded computation.Such systems fulfill two of Weiser’s key objectives—ubiquity, by injecting computation into the physi-cal world with high spatial density, and invisibility,by having the nodes and collectives of nodes oper-ate autonomously. Of particular importance to thetechnical community is making such pervasive com-puting itself pervasive. We need reusable buildingblocks that can help us move away from the spe-cialized instrumentation of each particular envi-ronment and move toward building reusable tech-niques for sensing, computing, and manipulatingthe physical world. The physical world presents an incredibly rich setof input modalities, including acoustics, image,motion, vibration, heat, light, moisture, pressure,ultrasound, radio, magnetic, and many more exoticmodes. Traditionally, sensing and manipulating theThis article addresses the challenges and opportunities ofinstrumenting the physical world with pervasive networks ofsensor-rich, embedded computation. The authors present ataxonomy of emerging systems and outline the enablingtechnological developments.REACHING FOR WEISER’ S VISIONDeborah Estrin University of California, Los AngelesDavid Culler and Kris PisterUniversity of California, BerkeleyGaurav Sukhatme University of Southern Californiaphysical world meant deploying and plac-ing a highly engineered collection of instru-ments to obtain particular inputs andreporting the data over specialized wiredcontrol protocols to data acquisition com-puters. Ubiquitous computing testbedshave retained much of this engineered dataacquisition style, although we use them toobserve a variety of unstructured phe-nomena (such as human gestures and inter-action). The opportunity ahead lies in theability to easily deploy flexible sensing,computation, and actuation capabilitiesinto our physical environments such thatthe devices themselves are general-purposeand can organize and adapt to support sev-eral application types.1In this article, we describe the challengeson the road ahead, present a taxonomy ofsystem types that we expect to emerge dur-ing this next decade of research and devel-opment, and summarize technologicaldevelopments. ChallengesThe most serious impediments to per-vasive computing’s advances are systemschallenges. The immense amount of dis-tributed system elements, limited physicalaccess to them, and this regime’s extremeenvironmental dynamics, when consideredtogether, imply that we must fundamen-tally reexamine familiar layers of abstrac-tion and the kinds of hardware accelera-tion employed—even our algorithmictechniques. Immense scaleA vast number of small devices will com-prise these systems. To achieve denseinstrumentation of complex physical sys-tems, these devices must scale down toextremely small volume, with applicationsformulated in terms of immense numbersof them. In five to 10 years, complete sys-tems with computing, storage, communi-cation, sensing, and energy storage couldbe as small as a cubic millimeter, but eachaspect’s capacity will be limited. Fidelityand availability will come from the quan-tity of partially redundant measurementsand their correlation, not the individualcomponents’ quality and precision.Limited accessMany devices will be embedded in theenvironment in places that are inaccessibleor expensive to connect with wires, mak-ing the individual system elements largelyuntethered, unattended, and resource con-strained. Much communication will bewireless, and nodes will have to rely on on-board and harvested energy (such as frombatteries and solar cells). Inaccessibility, aswell as sheer scale, implies that they mustoperate without human attendance; eachpiece is such a small part of the whole thatnobody can reasonably lay hands on all ofthem. At sufficient levels of efficiency,energy harvested from the environmentcan potentially allow arbitrary lifetimes,but the available energy bounds theamount of activity permitted per unit time.Energy constraints also limit the applica-tion space considerably; if solar power isused, nodes must be outdoors, and if bat-teries cannot be recharged, they will seri-ously affect maintenance, pollution, andreplacement costs.Extreme dynamicsBy virtue of nodes and the system as awhole being closely tied to the ever-chang-ing physical world, these systems will expe-rience extreme dynamics. By design, theycan sense their environment to provideinputs to higher-level tasks, and environ-mental changes directly affect their per-formance. In particular, environmental fac-tors dramatically influence propagationcharacteristics of low-power radio fre-quency