Towards the efficient use of LoRa for wireless sensor networks

Since their inception in 1998 with the Smart Dust Project from University of Berkeley, Wireless Sensor Networks (WSNs) had a tremendous impact on both science and society, influencing many (new) research fields, like Cyber-physical System (CPS), Machine to Machine (M2M), and Internet of Things (IoT). In over two decades, WSN researchers have delivered a wide-range of hardware, communication protocols, operating systems, and applications, to deal with the now classic problems of resourceconstrained devices, limited energy sources, and harsh communication environments. However, WSN research happened mostly on the same kind of hardware. With wireless communication and embedded hardware evolving, there are new opportunities to resolve the long standing issues of scaling, deploying, and maintaining a WSN. To this end, we explore in this work the most recent advances in low-power, longrange wireless communication, and the new challenges these new wireless communication techniques introduce. Specifically, we focus on the most promising such technology: LoRa. LoRa is a novel low-power, long-range communication technology, which promises a single-hop network with millions of sensor nodes. Using practical experiments, we evaluate the unique properties of LoRa, like orthogonal spreading factors, nondestructive concurrent transmissions, and carrier activity detection. Utilising these unique properties, we build a novel TDMA-style multi-hop Medium Access Control (MAC) protocol called LoRaBlink. Based on empirical results, we develop a communication model and simulator called LoRaSim to explore the scalability of a LoRa network. We conclude that, in its current deployment, LoRa cannot support the scale it is envisioned to operate at. One way to improve this scalability issue is Adaptive Data Rate (ADR). We develop two ADR protocols, Probing and Optimistic Probing, and compare them with the de facto standard ADR protocol used in the crowdsourced TTN LoRaWAN network. We demonstrate that our algorithms are much more responsive, energy efficient, and able to reach a more efficient configuration quicker, though reaching a suboptimal configuration for poor links, which is offset by the savings caused by the convergence speed. Overall, this work provides theoretical and empirical proofs that LoRa can tackle some of the long standing problems within WSN. We envision that future work, in particular on ADR and MAC protocols for LoRa and other low-power, long-range communication technologies, will help push these new communication technologies to main-stream status in WSNs

LoRa Transmission Parameter Selection

Low-Power Wide-Area Network (LPWAN) technologies such as Long Range (LoRa) are emerging that enable power efficient wireless communication over very long distances. LPWAN devices typically communicate directly to a sink node which removes the need of constructing and maintaining a complex multi-hop network. However, to ensure efficient and reliable communication LPWAN devices often provide a large number of transmission parameters. For example, a LoRa device can be configured to use different spreading factors, bandwidth settings, coding rates and transmission powers, resulting in over 6720 possible settings. It is a challenge to determine the setting that minimises transmission energy cost while meeting the required communication performance. This paper is the first to present a thorough analysis of the impact of LoRa transmission parameter selection on communication performance. We study in detail the impact of parameter settings on energy consumption and communication reliability. Using this study we develop a link probing regime which enables us to quickly determine transmission settings that satisfy performance requirements. The presented work is a first step towards an automated mechanism for LoRa transmission parameter selection that a deployed LoRa network requires, but is not yet specified within the Long Range Wide Area Network (LoRaWAN) framework

Autoinhibition of the formin Cappuccino in the absence of canonical autoinhibitory domains.

Formins are a conserved family of proteins known to enhance actin polymerization. Most formins are regulated by an intramolecular interaction. The Drosophila formin, Cappuccino (Capu), was believed to be an exception. Capu does not contain conserved autoinhibitory domains and can be regulated by a second protein, Spire. We report here that Capu is, in fact, autoinhibited. The N-terminal half of Capu (Capu-NT) potently inhibits nucleation and binding to the barbed end of elongating filaments by the C-terminal half of Capu (Capu-CT). Hydrodynamic analysis indicates that Capu-NT is a dimer, similar to the N-termini of other formins. These data, combined with those from circular dichroism, suggest, however, that it is structurally distinct from previously described formin inhibitory domains. Finally, we find that Capu-NT binds to a site within Capu-CT that overlaps with the Spire-binding site, the Capu-tail. We propose models for the interaction between Spire and Capu in light of the fact that Capu can be regulated by autoinhibition

LoRa for the Internet of Things

New transceiver technologies have emerged which enable power efficient communication over very long distances. Examples of such Low-Power Wide-Area Network (LPWAN)technologies are LoRa, Sigfox and Weightless. A typicalapplication scenario for these technologies is city wide meter reading collection where devices send readings at very low frequency over a long distance to a data concentrator (one-hop networks). We argue that these transceiversare potentially very useful to construct more generic Internet of Things (IoT) networks incorporating multi-hop bi-directional communication enabling sensing and actuation. Furthermore, these transceivers have interesting features notavailable with more traditional transceivers used for IoT networks which enable construction of novel protocol elements. In this paper we present a performance and capabilityanalysis of a currently available LoRa transceiver. We describe its features and then demonstrate how such transceivercan be put to use efficiently in a wide-area application scenario. In particular we demonstrate how unique featuressuch as concurrent non-destructive transmissions and carrier detection can be employed. Our deployment experiment demonstrates that 6 LoRa nodes can form a network covering 1.5 ha in a built up environment, achieving a potential lifetime of 2 year on 2 AA batteries and delivering data within 5 s and reliability of 80%

Hierarchical supercrystalline nanocomposites through the self-assembly of organically-modified ceramic nanoparticles

Biomaterials often display outstanding combinations of mechanical properties thanks to their hierarchical structuring, which occurs through a dynamically and biologically controlled growth and self-assembly of their main constituents, typically mineral and protein. However, it is still challenging to obtain this ordered multiscale structural organization in synthetic 3D-nanocomposite materials. Herein, we report a new bottom-up approach for the synthesis of macroscale hierarchical nanocomposite materials in a single step. By controlling the content of organic phase during the self-assembly of monodisperse organically-modified nanoparticles (iron oxide with oleyl phosphate), either purely supercrystalline or hierarchically structured supercrystalline nanocomposite materials are obtained. Beyond a critical concentration of organic phase, a hierarchical material is consistently formed. In such a hierarchical material, individual organically-modified ceramic nanoparticles (Level 0) self-assemble into supercrystals in face-centered cubic superlattices (Level 1), which in turn form granules of up to hundreds of micrometers (Level 2). These micrometric granules are the constituents of the final mm-sized material. This approach demonstrates that the local concentration of organic phase and nano-building blocks during self-assembly controls the final material's microstructure, and thus enables the fine-tuning of inorganic-organic nanocomposites' mechanical behavior, paving the way towards the design of novel high-performance structural materials.The authors gratefully acknowledge the financial support from the German Research Foundation (DFG) via the SFB 986-M3, projects A1, A6, Z2, and Z3. We thank Dr. F. Beckmann (Helmholtz-Zentrum Geesthacht, Geesthacht, Germany) for scanning the sample with the technique SRµCT and for reconstructing the slices, and Dr. I. Greving (Helmholtz-Zentrum Geesthacht, Geesthacht, Germany) for her inputs on SRµCT. Dr. F. Brun (National Institute of Nuclear Physics, Trieste, Italy) is acknowledged for the discussion regarding quantitative analysis using Pore3d

Adversarial Machine Learning in Smart Energy Systems

Smart Energy Systems represent a radical shift in the approach to energy generation and demand, driven by decentralisation of the energy system to large numbers of low-capacity devices. Managing this flexibility is often driven by machine learning, and requires real-time control and aggregation of these devices, involving a diverse set of companies and devices and creating a longer chain of trust. This poses a security risk, as it is sensitive to adversarial machine learning, whereby models are fooled through malicious input, either for financial gain or to cause system disruption. We show the feasibility of such an attack by analysing empirical data of a real system, and propose directions for future research related to detection and defence mechanisms for these kind of attacks

Very frequent physical aggression and vocalizations in nursing home residents with dementia

Objectives: We investigated the 2-week prevalence and correlates of very frequent physical aggression (PA) and vocalizations in nursing home (NH)-residents with dementia. Method/Design: This cross-sectional study used combined data of 2074 NH-residents from four studies, collected from 119 dementia special care units in 26 Dutch NH. Very frequent PA was defined as scoring 6 or 7 on the items ‘hitting’, pushing’, ‘biting’ and ‘kicking’ of the Cohen Mansfield Agitation Inventory; very frequent vocalizations as scoring 6 or 7 on ‘screaming’ and ‘making strange noises’. We compared NH-residents with very frequent PA or vocalizations with residents with less frequent PA or vocalizations, assessing correlates using univariate and multivariate multilevel logistic regression analyses. Results: We found a 2-week prevalence of 2.2% (95% confidence interval (CI): 1.63–2.89) of very frequent PA and 11.5% of very frequent vocalizations (95% CI: 10.23–12.98). Very frequent PA was only associated with apathy (odds ratio (OR)=1.93, 95% CI: 1.04–3.61). Correlates of very frequent vocalizations were age (OR = 0.97, 95% CI: 0.951–0.998), dementia severity (overall p-value 0.020), antipsychotic drug use (OR = 1.56, 95% CI: 1.08–2.26), antiepileptic drug use (OR = 2.75, 95% CI: 1.34–5.68) and euphoria (OR = 2.01, 95% CI: 1.22–3.31). Conclusion: Characteristics of NH-residents with very frequent PA or very frequent vocalizations differ from those of NH-residents with less frequent PA or vocalizations. Frontal lobe damage, boredom, pain and/or external factors may explain several of the found associations, but further research is necessary. Our findings may contribute to better care for these residents and thereby to improving their quality of life

Trends in the burden of HIV mortality after roll-out of antiretroviral therapy in KwaZulu-Natal, South Africa: an observational community cohort study.

Antiretroviral therapy (ART) substantially decreases morbidity and mortality in people living with HIV. In this study, we describe population-level trends in the adult life expectancy and trends in the residual burden of HIV mortality after the roll-out of a public sector ART programme in KwaZulu-Natal, South Africa, one of the populations with the most severe HIV epidemics in the world. Data come from the Africa Centre Demographic Information System (ACDIS), an observational community cohort study in the uMkhanyakude district in northern KwaZulu-Natal, South Africa. We used non-parametric survival analysis methods to estimate gains in the population-wide life expectancy at age 15 years since the introduction of ART, and the shortfall of the population-wide adult life expectancy compared with that of the HIV-negative population (ie, the life expectancy deficit). Life expectancy gains and deficits were further disaggregated by age and cause of death with demographic decomposition methods. Covering the calendar years 2001 through to 2014, we obtained information on 93 903 adults who jointly contribute 535 42 8 person-years of observation to the analyses and 9992 deaths. Since the roll-out of ART in 2004, adult life expectancy increased by 15·2 years for men (95% CI 12·4-17·8) and 17·2 years for women (14·5-20·2). Reductions in pulmonary tuberculosis and HIV-related mortality account for 79·7% of the total life expectancy gains in men (8·4 adult life-years), and 90·7% in women (12·8 adult life-years). For men, 9·5% is the result of a decline in external injuries. By 2014, the life expectancy deficit had decreased to 1·2 years for men (-2·9 to 5·8) and to 5·3 years for women (2·6-7·8). In 2011-14, pulmonary tuberculosis and HIV were responsible for 84·9% of the life expectancy deficit in men and 80·8% in women. The burden of HIV on adult mortality in this population is rapidly shrinking, but remains large for women, despite their better engagement with HIV-care services. Gains in adult life-years lived as well as the present life expectancy deficit are almost exclusively due to differences in mortality attributed to HIV and pulmonary tuberculosis. Wellcome Trust, the Bill & Melinda Gates Foundation, and the National Institutes of Health