A two phase hybrid RSS/AoA algorithm for indoor device localization using visible light

Ubiquitous computing as the integration of sensors, smart devices, and intelligent technologies to form a “smart space” environment relies on the development of both middleware and networking technologies. Several kinds of smart space middleware have been developed and OSGi (Open Service Gateway Initiative) was initiated mainly for interoperability support with service distribution among various middleware environments. In this paper, we analyze the weaknesses in the OSGi service platform such as a non-distributed framework, passive user management, device management, and service bundle management. Moreover, we propose that in a smart space environment, Location-aware SBM (Service Bundle Manager) is most capable of efficiently managing various service bundles. This paper concludes with the implementation results for the SBM.

This paper describes LocMAC, a new location aware power saving MAC layer for target tracking applications in smart space environments. Target tracking applications focus on providing proximity based local services to mobile users within a fixed deployment of wireless nodes. Conventional wireless sensor MAC layers increase the lifespans of battery powered wireless nodes by scheduling sleep periods for the entire network, which are either of fixed length, or vary based upon current network metrics. LocMAC bases its sleep schedule on the relative physical location of network nodes and allows target tracking service to be guaranteed. It propagates user location updates, and uses this knowledge to perform 'location based sleep scheduling' (LBSS). LBSS describes the use of wireless node and network target positions to maximise the potential sleep periods. Adding knowledge of user mobility allows those nodes which will not be required by the network application to sleep for longer periods of time, waking up just in time to service network user requirements. The paper describes the operation of LocMAC and compares its performance against existing sleep scheduling MAC protocols through analysis and simulations of typical application scenarios. The results show that LocMAC performs significantly better for target tracking applications and is particularly appropriate for use in future Smart Spaces.

Aims. Metis is the first solar coronagraph designed for a space mission and is capable of performing simultaneous imaging of the off-limb solar corona in both visible and UV light. The observations obtained with Metis aboard the Solar Orbiter ESA-NASA observatory will enable us to diagnose, with unprecedented temporal coverage and spatial resolution, the structures and dynamics of the full corona in a square field of view (FoV) of ±2.9° in width, with an inner circular FoV at 1.6°, thus spanning the solar atmosphere from 1.7R⊙to about 9R⊙, owing to the eccentricity of the spacecraft orbit. Due to the uniqueness of the Solar Orbiter mission profile, Metis will be able to observe the solar corona from a close (0.28 AU, at the closest perihelion) vantage point, achieving increasing out-of-ecliptic views with the increase of the orbit inclination over time. Moreover, observations near perihelion, during the phase of lower rotational velocity of the solar surface relative to the spacecraft, allow longer-term studies of the off-limb coronal features, thus finally disentangling their intrinsic evolution from effects due to solar rotation.Methods. Thanks to a novel occultation design and a combination of a UV interference coating of the mirrors and a spectral bandpass filter, Metis images the solar corona simultaneously in the visible light band, between 580 and 640 nm, and in the UV H ILyman-αline at 121.6 nm. The visible light channel also includes a broadband polarimeter able to observe the linearly polarised component of the K corona. The coronal images in both the UV H ILyman-αand polarised visible light are obtained at high spatial resolution with a spatial scale down to about 2000 km and 15 000 km at perihelion, in the cases of the visible and UV light, respectively. A temporal resolution down to 1 s can be achieved when observing coronal fluctuations in visible light.Results. The Metis measurements, obtained from different latitudes, will allow for complete characterisation of the main physical parameters and dynamics of the electron and neutral hydrogen/proton plasma components of the corona in the region where the solar wind undergoes the acceleration process and where the onset and initial propagation of coronal mass ejections (CMEs) take place. The near-Sun multi-wavelength coronal imaging performed with Metis, combined with the unique opportunities offered by the Solar Orbiter mission, can effectively address crucial issues of solar physics such as: the origin and heating/acceleration of the fast and slow solar wind streams; the origin, acceleration, and transport of the solar energetic particles; and the transient ejection of coronal mass and its evolution in the inner heliosphere, thus significantly improving our understanding of the region connecting the Sun to the heliosphere and of the processes generating and driving the solar wind and coronal mass ejections.Conclusions. This paper presents the scientific objectives and requirements, the overall optical design of the Metis instrument, the thermo-mechanical design, and the processing and power unit; reports on the results of the campaigns dedicated to integration, alignment, and tests, and to the characterisation of the instrument performance; describes the operation concept, data handling, and software tools; and, finally, the diagnostic techniques to be applied to the data, as well as a brief description of the expected scientific products. The performance of the instrument measured during calibrations ensures that the scientific objectives of Metis can be pursued with success.

The experience of full automation without explicit user direction may induce anxiety among smart space users. The use of explicit mediators between users and fully automated systems may help to mitigate users’ anxiety. While robots mediators are one possible solution, several issues remain, including high complexity and limited collaboration between robots and smart space platforms, reducing overall system reliability. This paper proposes the Integrated Control Architecture for Robotic mediator in Smart environments (ICARS) as a solution to improve the integration and reliability of robot mediators within automated smart spaces. Assuming relatively thin network robots as robotic mediators to enable a wide distribution with less cost, ICARS provides a well-organized software framework consisting of three layers to integrate robots and smart spaces: a flexible communication/device model, an adaptive service model for the integrated robot control architecture, and a behavior-based high-level collaboration model. In this paper, we also present details of the design, implementation, and an application scenario conducted with ICARS. The results show that ICARS enables flexible integration of the diverse devices associated with robots and environments, adaptive service provision for collaborative services, and easier development of high-level collaborative applications with decent performance.

Stakeholders in disaster management settings often find the effective and efficient utilisation of emerging technologies quite a challenging process but very frequently a critical computational inclusion to the intelligence required for protecting individuals, communities, their environment and critical infrastructures. The special issue is dedicated to the dissemination of original contributions that are related to the theories, practices and concepts of smart environments and emerging collective computational and collaborative technologies for the specific purpose of improving intelligence when managing natural or man-made disasters. In particular, the special issue is focused on the applicability—for the purpose of managing disasters—of technologies that can support autonomous adaptation to complex and messy situations caused from these, highly dynamic contexts. Various methods and technologies including simulations, multi-dimensional decision modeling, data mining, swarm intelligence, smart spaces and sensors, contextaware, situated and pervasive computing, geographical information systems, ad-hoc mobile networks, wireless communications, grid and cloud computing, social networks and crowd sourcing are a smart technology means to enable a more informed decision making to mitigate and prepare for, respond to and recover from growing occurrences of disasters. This special issue comprises six articles, which have been selected after a careful review process. Specifically, this is a collection of extended versions of papers presented either at the Smart Environments for Disaster Management (SEDM-2011) workshop which run in conjunction with the 6th 3PGCIC-2011, held on October 26–28, 2011 in Barcelona, Spain or at the Computational Intelligence for Disaster Management (CIDM-2011) workshop which run in conjunction with the 3rd INCoS 2011, held on November 30–December 2, 2011 in Fukuoka, Japan. In the first article, Li explains that mobility is an important issue that deters people living in remote areas and elderlies to visit health clinics on a regular basis; this is also the case for individuals with disabilities. Advances in information and telecommunication technologies have been made telemedicine possible. By using the latest sensor technologies, a person’s vital data can be collected in a smart home environment. The bio-information can then be transferred wirelessly or via the Internet to medical databases and the healthcare professionals. The article surveys and compiles the state-of-the-art smart home technologies and telemedicine systems. In the second article, Sakanushi et al. discuss concerns with triage tags, which are widely used at disaster scenes. Some of these concerns include the inability to show the current priorities of casualties and a failure to collect the physiological conditions of the casualties. In their article, authors propose an electronic triage which continuously monitor the vital signs of casualties and transmit them to an electronic triage server. Experimental results show that their proposed electronic triage system can save more lives than the paper triage tags version. In the third article, Furey et al. explain that the use of Wi-Fi signals is an attractive and reasonably affordable option to deal with the currently unsolved problem of widespread tracking in an indoor environment. In their article, authors present a system which aims at overcoming N. Bessis (&) E. Asimakopoulou School of Computing and Mathematics, University of Derby, Kedleston Road, Derby DE22 1GB, UK e-mail: n.bessis@derby.ac.uk

Life cycle management plays an essential role in context-aware systems, it needs to aware surrounding contexts and adapt to changing contexts in highly dynamic environments. Consequently, context management is different from traditional approaches due to the characteristics of contextual information are dynamic, transient, and fallible. Understanding the life cycle of a context is the key issue to maintain consistent contextual information. Accordingly, we propose an ontology-based model for representing, deducing, and managing consistent contextual information. In addition, an agent-based architecture supports the process of context life cycle management.

Spectrum scarcity of traditional radio communication has led communication engineers to find new alternatives. Indoor visible light communication is one alternative to solve this problem since its spectrum is not regulated and it has much wider bandwidth then traditional communication systems. This increased the research done in the field of visible light communications. However a proper indoor channel model is lacking and all previous studies assumes that only additive white Gaussian noise (AWGN) is present. Lack of proper channel model has motivated us to model a realistic indoor visible light channel. After modeling the indoor visible light channel, the performance of an asymmetrically clipped optical OFDM (ACOOFDM) system which is suitable for optical communications is investigated and compared to that of the AWGN optical channels.

In smart environments, indoor positioning systems provide several options for smart computing users, businesses, and industries, thereby dramatically enhancing human well-being and productivity. Smart homes and smart indoor environments are prominent emerging technologies in the Internet of Things era and future communications, with applications such as providing personalized healthcare to the elderly and those with impairments by connecting them to the world via high-speed wireless communication infrastructure. This study offers a new approach to real-time indoor positioning using passive RFID technology to estimate the real-time location of smart home users based on their movements in smart environment space. An experimental indoor positioning system technique intends to improve assisted living and identify daily activities in a smart environment. To demonstrate this, we conducted a case study on indoor positioning using RFID technology. The experimental investigation is based on a location-based system that leverages the creation of deep learning algorithms in conjunction with radio signal strength indicator (RSSI) measurements of passive RFID-tagged devices. The proposed architecture encourages more precise identification of smart home objects and the ability to precisely locate users in real-time with good measured precision while minimizing technical and technological barriers to the adoption of location-based technologies in the daily lives of smart environment inhabitants. This will eventually facilitate the realization of location-based Internet of Things (IoT) systems.

Context.We present the results for the in-flight radiometric calibration performed for the Visible Light (VL) channel of the Metis coronagraph on board Solar Orbiter.Aims.The radiometric calibration is a fundamental step in building the official pipeline of the instrument, devoted to producing the calibrated data in physical units (L2 data).Methods.To obtain the radiometric calibration factor (ϵVL), we used stellar targets transiting the Metis field of view. We derivedϵVLby determining the signal of each calibration star by means of the aperture photometry and calculating its expected flux in the Metis band pass. The analyzed data set covers the time range from the beginning of the Cruise Phase of the mission (June 2020) until March 2021.Results.Considering the uncertainties, the estimated factorϵVLis in a good agreement with that obtained during the on-ground calibration campaign. This implies that up to March 2021 there was no measurable reduction in the VL channel throughput. Finally, we compared the total and polarized brightness visible light images of the solar corona acquired with Metis and STEREO-A/COR2 during the November 2020 superior conjunction of these instruments. A general good agreement was obtained between the images of these instruments for both the total and polarized brightness.

Ubiquitous computing as the integration of sensors, middleware, and networking technologies to form a "smart space" environment relies on the development of both software and hardware solutions. For over 3 years, our group has been developing a smart-space environment, involving the exploration of core technologies and attractive applications. We introduce the challenges faced and lessons learned in designing and developing a smart-space environment, including device control services, locating systems, wireless sensor nodes, and middleware services.

Network accounting, forensics, security, and performance monitoring applications often need to examine detailed traces from subsets of flows ("subpopulations"), where the application desires flexibility in specifying the subpopulation (e.g., to detect a portscan, the application must observe many packets between a source and a destination with one packet to each port). However, the dynamism and volume of network traffic on many high-speed links necessitates traffic sampling, which adversely affects subpopulation monitoring: because many subpopulations of interest to operators are low-volume flows, conventional sampling schemes (e.g., uniform random sampling) miss much of the subpopulation's traffic. Today's routers and network devices provide scant support for monitoring specific traffic subpopulations.

Nowadays, location awareness becomes the key to numerous Internet of Things (IoT) applications. Among the various methods for indoor localisation, received signal strength indicator (RSSI)-based fingerprinting attracts massive attention. However, the RSSI fingerprinting method is susceptible to lower accuracies because of the disturbance triggered by various factors from the indoors that influence the link quality of radio signals. Localisation using body-mounted wearable devices introduces an additional source of error when calculating the RSSI, leading to the deterioration of localisation performance. The broad aim of this study is to mitigate the user’s body shadowing effect on RSSI to improve localisation accuracy. Firstly, this study examines the effect of the user’s body on RSSI. Then, an angle estimation method is proposed by leveraging the concept of landmark. For precise identification of landmarks, an inertial measurement unit (IMU)-aided decision tree-based motion mode classifier is implemented. After that, a compensation model is proposed to correct the RSSI. Finally, the unknown location is estimated using the nearest neighbour method. Results demonstrated that the proposed system can significantly improve the localisation accuracy, where a median localisation accuracy of 1.46 m is achieved after compensating the body effect, which is 2.68 m before the compensation using the classical K-nearest neighbour method. Moreover, the proposed system noticeably outperformed others when comparing its performance with two other related works. The median accuracy is further improved to 0.74 m by applying a proposed weighted K-nearest neighbour algorithm.

The effects of aggregated land cover data on estimating NPP in northern Wisconsin

Intelligent personal devices interacting with smart spaces will create a world where your environment itself anticipates and is ready to serve your every need. Many disciplines and technologies are realizing this vision of context awareness, which was science fiction just 25 years ago. In particular, your smartphone will evolve into your “sixth” sense — autonomously alerting you to your environment and notifying your social network of your interests, concerns and goals. Research challenges include ultra-low power always-on sensing and inference technologies, near-zero overhead peer-to-peer networking, and automated reasoning. Models derived from deep learning and knowledge-based reasoners in the proximate cloud will combine to create sentient immersive spaces. Advances in low power silicon, energy harvesting and scavenging will ensure that these smart environments are sustainable. This panel brings together leading experts to tell us about what sixth-sense functions are round the corner and what further breakthroughs are needed to realize this contextual awareness vision.

The RFID is considered to provide an efficient solution to merge physical world with virtual space for pervasive computing. The wireless sensor network (WSN) is also a feasible and cost-effective candidate for the context sensing in the pervasive computing. We propose a smart space named SmartExhibtion as an scenario where the RFID is integrated to the sensor network and describe the whole architecture together with the application mode. Moreover, we detail the design of the ZigBee-based RFID network for experiment as well as the hardware implementation and the software protocol of the network node - RFSenMote. The characteristic of the paper is that the RFID is extended into sensor network in an actual application scenario and an embedded device which integrates RFID with WSN for the test platform is developed. This integration enables the traits such as self-configuration, random deployment, low-cost and interoperability which are adaptive to the smart space of the pervasive computing. In addition to RFID, the wireless sensor network offers the ability to detect and record contextual changes in the smart environment.