Academic literature on the topic 'Self-Configuring lighting'

Reflectance Transformation Imaging (RTI) is a computational photographic method that captures an object’s surface shape & color and enables the interactive re-lighting of the subject from any direction. RTI model of an object is built from multiple images of it captured by a stationary camera but varying light directions. By changing the direction of the light, the respective micro-geometry of the object is highlighted. The RTI acquisition process is often long, and tedious when it is not automated. It requires expertise to define for each analysed object which are the number and the relevant lighting positions in the acquisition sequence. In this paper, we present our novel Next Best Light Position (NBLP) method to address this issue. The proposed method is based on the principle of a gradient descent allowing in an adaptive and iterative way, to automatically define the most appropriate lighting directions for the RTI acquisition of an object/surface.

The Internet of Things (IoT) will bring together billions of devices, denoted as Smart Objects (SOs), in an Internet-like architecture. Typically, SOs are embedded devices with severe constraints in terms of processing capabilities, available memory (RAM/ROM), and energy consumption. SOs tend to be deployed in environments in which the human intervention is not suitable or needs to be minimized (e.g., smart city maintenance). They must adapt to the surrounding environment by self-configuring: to this end, several mechanisms have been proposed (e.g., UPnP, ZeroConf, etc.). In this paper, we focus on IEEE 802.15.4 networks with IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) adaptation layer, where IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is the routing protocol of choice. In this context, we propose a lightweight RPL-based mechanism to Resource Discovery (RD) and Service Discovery (SD), denoted as DiRPL. In particular, DiRPL exploits the RPL handshake to detect new nodes in the network; resources are then simply discovered with a Constrained Application Protocol (CoAP) request and can thus be published in a local resource directory. A very attractive feature of the proposed DiRPL approach is that it builds on well-defined and well-known standard protocols. The performance of the proposed system is investigated with WisMote nodes deployed inside the Cooja simulator, running the Contiki operating system. Practical application scenarios to large-scale smart city monitoring, such as smart lighting and large-scale water consumption monitoring, are investigated.

The Garden of Eden is the original surveillance state. God creates the heavens and the earth, turns on the lights, inspects everything that he has made and, behold, finds it very good. But then the creation attempts to acquire the surveillant properties of the creator. In Genesis 3, a serpent explains to Eve the virtues of forbidden fruit: “Ye shall not die: For God doth know that in the day ye eat thereof, then your eyes shall be opened, and ye shall be as gods, knowing good and evil” (Genesis 3: 4–5). Adam’s and Eve’s eyes are certainly opened (sufficiently so to necessitate figleaves), but in the next verse, God’s superior surveillance system has found them out. The power relationship Genesis illustrates has prompted many – the Romantics in their seditious appropriations of Paradise Lost, for instance – to question whether Eden is all that “good” after all. Why was God so concerned for Eve and Adam not to see? For that matter, why was he not there to intercept the serpent, but so promptly on the scene of humanity’s crime? Various answers (that God planned the Fall because it would enable him to demonstrate supreme love through Jesus, that Eve and Adam were wilfully wrong to grasp for equality with the Creator of the Universe, that God could not intervene in the temptation because it would compromise humanity’s free will) do not alter the flaw in God’s perfect garden state. Consciousness of this imperfection surfaces repeatedly in Western utopian narratives. The very existence of such narratives points to a humanist distrust in God as social engineer; the fact that these secular Edens are themselves often flawed suggests both a parody of the original Eden and an admission that humans are not up to the task of social engineering either. Thomas More’s Utopia and Ridley Scott’s Blade Runner – one the ostensible depiction of a new Eden, the other an outright dystopic inferno – address the association of Eden (or the Creator) with surveillance, and so undermine the ideality of the prelapsarian Garden. The archetypal power relationship, that of All-Seeing Creator with always-seen creation, is reconfigured sans God: in Utopia, with society itself performing the work of a transcendent surveillance system; in Blade Runner, with the multi-planetary Tyrell corporation doing so. In both cases, the Omnisurveillant is stripped of the mitigating quality of being God, and so exposed as oppressive, unjust, an affront to the idea of perfection. Like Eden, the eponymous island of Thomas More’s Utopia is a surveillance state. Glass, we read, “is there much used” (More 55). Surveillance is decentralised and patriarchal: wives are expected to confess to their husbands, children to their mothers (More 65). Each year, every thirty families select a “syphogrant”, whose “chief and almost … only office … is to see and take heed that no man sit idle, but that every one apply his own craft with earnest diligence” (More 57). In the mess halls, “The Syphogrant and his wife sit in the midst of the high table … because from thence all the whole company is in their sight” (More 66). Elders are ranged amongst the young men so that “the sage gravity and reverence of the elders should keep the youngsters from wanton licence of words and behaviour. Forasmuch as nothing can be so secretly spoken or done at the table, but either they that sit on the one side or on the other must needs perceive it” (More 66). Not only are the Utopians subject to social surveillance, but also to a conviction of its inescapability. Believing that the dead move among them, the Utopians feel that they are being watched (even when they are not) and thus regulate their own behaviour. In his preface to The Panopticon, Jeremy Bentham extols the virtues of his surveillance machine: “Morals reformed – health preserved – industry invigorated instruction diffused – public burthens lightened – Economy seated, as it were, upon a rock – the gordian knot of the Poor-Laws are not cut, but untied – all by a simple idea in Architecture!” (Bentham 29). As Foucault points out in “Panopticism”, the Panopticon works so well because the prisoner can never know when she or he is being watched, and this uncertainty compels the prisoner into constant discipline. Atheist Bentham had created a transcendent surveillance system that would replace God in (he trusted) an increasingly secular society. Bentham’s catalogue of the Panopticon’s benefits is something of a Utopian manifesto in its own right, and his utilitarianism, based on the “greatest-happiness principle”, was prepared to embrace the surveillance system so long as that system maximised overall happiness. Perhaps Thomas More was a proto-utilitarian, prepared to take up the repressive aspects of panopticism in exchange for moral reform, health preservation, the invigoration of industry and the lightening of public burdens. On the other hand, Utopia is widely read as a deliberately ironic representation of the ideal state. Stephen Greenblatt has pointed out that More “remained ambivalent about many of his most intensely felt perceptions” in Utopia, and he offers the text’s various ironising elements (such as the name of More’s fictitious interlocutor, Hythlodaeus, “well learned in nonsense”) as evidence (Greenblatt 54). Even the text’s title undermines its Edenic vision: as Louis Marin argues, “Utopia” could derive equally from Greek ou-topos, no-place, or eu-topos, good-place (Marin 85). More’s ambivalence about Utopia – to the extent of attributing his account of No-place to a character called Nonsense – suggests his impatience with his own flawed social vision. While Utopia is ambivalent in its depiction of the perfect state, more recent utopian narratives – Aldous Huxley’s Brave New World (1931), for instance, or George Orwell’s Nineteen Eighty-Four (1949) – are unequivocally ironic about the subordination of the individual to the perfect state. The Bible’s account of human society begins with Eden and ends with Apocalypse, in which divine surveillance reaches its inevitable conclusion in divine judgement. The utopian genre has undergone a very similar trajectory, beginning with what seem to be sincere attempts to sketch the perfect state, briefly flourishing as Europeans became first aware of Cytherean islands in the South Pacific, and, more recently, representing outright apocalypse (as in Margaret Atwood’s The Handmaid’s Tale [1986] and Ridley Scott’s Blade Runner [1992]), or at least responding pessimistically to human attempts at social engineering. Blade Runner’s dystopic inversion of biblical creation illustrates an enduring distrust in both human and divine attempts to establish Eden. The year is 2019 (only one year off 2020, perfect vision); the place is Los Angeles, the City of Angels. Corporate biomechanic Eldon Tyrell manufactures a race of robots, “replicants”, who are physically indistinguishable from humans, capable of developing emotional responses, but burdened with a four-year self-destruct mechanism. When the replicants rebel, their leader, Roy Batty, demands of Tyrell, “I want more life, Father”. Tyrell is not only “Father”, but “the god of biomechanics”; and Batty is simultaneously a reworking of Adam (the disaffected creation), Lucifer (the rebel angel) and Christ (as shown in the accompanying iconography of crucifixion and doves). The Bible’s leading actors are all present, but the City of Angels, 2019, is unmistakeably not Eden. It is a polluted, dank, flame-spewing dragon of a city, more Inferno than human habitation. The film’s oppressive film noir atmosphere relays the nausea induced by the Tyrell Corporation’s surveillance system. The Voight-Kamff test – a means of assessing emotional response (and thus determining whether an individual is human or replicant) by scanning the pupils – is a surveillance mechanism so intrusive it measures not only behaviour, but feelings. The optical imagery throughout the film reinforces the idea of permanent visibility. The result is a claustrophobic paranoia. Blade Runner is unambiguous in its pessimism about human attempts to regulate society (attempts which it shows to be reliant on surveillance, slavery and swift punishment). It seems unlikely that the God of Genesis is specifically targeted by this film’s parody of the Creator-creation power relationship – its critiques of capitalism and environmental mismanagement are much more overt – but by configuring its dramatis personae in biblical roles, Blade Runner demonstrates that the paradigm for omnisurveillant creators comes from the Bible. In turn, by placing Los Angeles, 2019, at such a distant aesthetic remove from Eden, the film portrays the omnisurveillant creator unrelieved by natural beauty. Foucault’s formulation of panopticism, that power is seeing without being seen, that being seen without seeing is disempowerment, informs all three texts – Genesis, Utopia and Blade Runner. What differentiates them, determines how perfect each text would have its world believed to be, is the extent to which its authors approve this power relationship. References Bentham, Jeremy. The Panopticon; or, The Inspection House (1787). In The Panopticon Writings. Ed. Miran Bozovic. London: Verso, 1995. 29-95. Foucault, Michel. “Panopticism”. In Discipline and Punish: the Birth of the Prison. Trans. Alan Sheridan (1977). New York: Vintage Books, 1995. 195–228. Greenblatt, Stephen. Renaissance Self-Fashioning: From More to Shakespeare. Chicago and London: U of Chicago P, 1980. Marin, Louis. Utopics: The Semiological Play of Textual Spaces. Trans. Robert A. Vollrath. Atlantic Highlands, NJ: Humanities Press International, 1990. More, Thomas. Utopia (1516). In Susan Brice, ed. Three Early Modern Utopias: Utopia, New Atlantis, The Isle of Pines. Oxford: Oxford UP, 1996. Scott, Ridley. Blade Runner: The Director’s Cut. United States, 1992. Citation reference for this article MLA Style Harley, Alexis. "Resurveying Eden: Panoptica in Imperfect Worlds." M/C Journal 8.4 (2005). echo date('d M. Y'); ?> <http://journal.media-culture.org.au/0508/02-harley.php>. APA Style Harley, A. (Aug. 2005) "Resurveying Eden: Panoptica in Imperfect Worlds," M/C Journal, 8(4). Retrieved echo date('d M. Y'); ?> from <http://journal.media-culture.org.au/0508/02-harley.php>.

Cette thèse de doctorat est réalisée dans le cadre d'un contrat de recherche entre la Société Eclatec, concepteur et fabricant français de luminaires urbains, et l'Institut Jean Lamour de Nancy. L'objectif concerne l'amélioration de l'éclairage nocturne des villes tout en réduisant la consommation électrique et la pollution lumineuse. Pour cela une caméra RGB est intégrée à la source lumineuse du lampadaire. Elle constitue le principal point de collecte d'informations. Ce choix a imposé l'utilisation d'une optique très grand angle dont l'axe est faiblement incliné par rapport à la verticale. La configuration adoptée permet d'observer en grande partie la zone éclairée par le luminaire mais se traduit par des images très déformées. A partir de ce système 4 grandes problématiques ont été étudiées. La première concerne la détection vidéo des usagers à proximité du luminaire dans des conditions de très faible éclairement afin d'assurer une gradation dynamique de l'éclairage. Cette détection exploite les modèles de deep learning de la famille Yolo que nous avons ré-entrainés par transfert learning sur une collection d'images spécifiques. Celles-ci ont été relevées en différents points de l'agglomération nancéenne à une hauteur de 6 à 8 m. Pour une scène éclairée sous 10 lux, une ouverture photographique à f/3.5 et une sensibilité fixée à 3200 ISO, le taux de détection des piétons et véhicules est supérieur à 97 %. Le modèle, implanté sur le GPU embarqué NVidia Jetson nano, permet d'atteindre une cadence d'environ 10 FPS qui reste suffisante pour notre application. La deuxième orientation étudie la reconnaissance de l'environnement autour du luminaire au moyen d'une segmentation sémantique de images. Cette segmentation sera exploitée ultérieurement pour adapter la distribution lumineuse de la matrice de leds à la situation urbaine rencontrée. Pour ce faire, nous avons fait appel au réseau de neurones OCR-HRNet qui améliore la segmentation haute résolution par l'ajout d'une représentation contextuelle tenant compte de l'agrégation des pixels. Cette architecture s'avère bien adaptée aux images de surfaces peu homogènes qui caractérisent le sol sous le luminaire. Les résultats montrent une très bonne identification des constructions et des zones végétalisées. La séparation trottoir/route reste encore délicate notamment lorsque les revêtements des voies de circulation présentent des réflectances et textures similaires. Une solution par marquage virtuel à postériori des images améliore sensiblement la précision de la segmentation notamment dans le cas de scènes ensoleillées qui présentent de nombreuses zones d'ombre. Dans un troisième temps nous avons modélisé le système optique afin de permettre une estimation de la position réelle des points du sol à partir de leur image. Une transformation Cam To World simple est proposée. Celle-ci prend en compte les paramètres extrinsèques de la prise de vue (hauteur, pitch et résolution) et la fonction de distorsion de la lentille dont la projection optique est assimilée à une loi équidistante. La précision requise n'étant pas critique, la calibration rigoureuse du système n'a pas été effectuée. Pour une zone d'observation effective de 20 m × 50 m, l'erreur de localisation est de l'ordre du mètre. Enfin nous proposons une piste d'exploitation du parc de luminaires pour l'analyse de la fluidité du trafic routier. La méthode proposée analyse le mouvement apparent des usagers par estimation du flot optique moyen dans chacune des boites englobantes détectées par Yolo. La détermination du flot optique est actuellement réalisée en mode hors ligne par l'algorithme de deep learning FlowNet2. Dans la gamme de 0 à 15 m/s la vitesse estimée du mobile présente une erreur inférieure à 1 m/s
This doctoral thesis has been conducted within the framework of a research contract between the French urban lighting design and manufacturing company, Eclatec, and the Jean Lamour Institute in Nancy. The overarching goal of this research is to enhance nighttime urban lighting while simultaneously reducing electrical consumption and light pollution. To achieve this, an RGB camera is integrated into the streetlamp's light source, serving as the primary data collection point. This choice necessitated the use of a wide-angle lens with a slight vertical tilt in its axis. Although this configuration allows for the observation of a significant portion of the illuminated area, it results in highly distorted images. From this system, four major research challenges were investigated:1. The first challenge concerns video detection of individuals in close proximity to the luminaire under very low lighting conditions, with the aim of achieving dynamic lighting adjustment. This detection relies on deep learning models from the Yolo family, which were fine-tuned through transfer learning using a specific collection of images. These images were captured at various locations in the Nancy metropolitan area, at heights ranging from 6 to 8 meters. Under conditions of 10 lux illumination, an aperture of f/3.5, and a fixed sensitivity of 3200 ISO, the detection rate for pedestrians and vehicles exceeds 97%. The model, implemented on the embedded NVidia Jetson Nano GPU, achieves a frame rate of approximately 10 FPS, which proves adequate for our application. 2. The second research direction explores the recognition of the environment surrounding the luminaire through semantic segmentation of images. This segmentation will subsequently be employed to adapt the light distribution of the LED matrix to the encountered urban scenario. To accomplish this, we employed the OCR-HRNet neural network, which enhances high-resolution segmentation by incorporating contextual representation that considers pixel aggregation. This architecture is well-suited to images of non-uniform surfaces, characteristic of the ground beneath the luminaire. The results demonstrate excellent identification of structures and vegetated areas. However, the distinction between sidewalk and road remains challenging, particularly when road surfaces exhibit similar reflectance and textures. A post-image virtual marking solution significantly improves segmentation accuracy, especially in sunny scenes with numerous shadowed areas. 3. In a third phase, we modeled the optical system to enable the estimation of the real-world positions of ground points based on their images. A simple Cam To World transformation is proposed, accounting for extrinsic parameters of the viewpoint (height, pitch, and resolution), and the lens distortion function, approximated as an equidistant projection law. Given that stringent precision is not critical, a rigorous system calibration was not conducted. For an effective observation zone of 20 m × 50 m, the localization error is on the order of meters. 4. Finally, we propose an avenue for utilizing the lighting infrastructure to analyze traffic flow fluidity. The proposed method analyzes apparent motion of users by estimating the mean optical flow within each bounding box detected by Yolo. Currently, optical flow determination is performed offline using the deep learning algorithm FlowNet2. In the range of 0 to 15 m/s, the estimated speed of the moving object exhibits an error of less than 1 m/s

abstract: Lighting systems and air-conditioning systems are two of the largest energy consuming end-uses in buildings. Lighting control in smart buildings and homes can be automated by having computer controlled lights and window blinds along with illumination sensors that are distributed in the building, while temperature control can be automated by having computer controlled air-conditioning systems. However, programming actuators in a large-scale environment for buildings and homes can be time consuming and expensive. This dissertation presents an approach that algorithmically sets up the control system that can automate any building without requiring custom programming. This is achieved by imbibing the system self calibrating and self learning abilities. For lighting control, the dissertation describes how the problem is non-deterministic polynomial-time hard(NP-Hard) but can be resolved by heuristics. The resulting system controls blinds to ensure uniform lighting and also adds artificial illumination to ensure light coverage remains adequate at all times of the day, while adjusting for weather and seasons. In the absence of daylight, the system resorts to artificial lighting. For temperature control, the dissertation describes how the temperature control problem is modeled using convex quadratic programming. The impact of every air conditioner on each sensor at a particular time is learnt using a linear regression model. The resulting system controls air-conditioning equipments to ensure the maintenance of user comfort and low cost of energy consumptions. The system can be deployed in large scale environments. It can accept multiple target setpoints at a time, which improves the flexibility and efficiency of cooling systems requiring temperature control. The methods proposed work as generic control algorithms and are not preprogrammed for a particular place or building. The feasibility, adaptivity and scalability features of the system have been validated through various actual and simulated experiments.
Dissertation/Thesis
Doctoral Dissertation Computer Science 2015