Offloading SLAM for Indoor Mobile Robots with Edge-Fog-Cloud Computing

Indoor mobile robots are widely used in industrial environments such as large logistic warehouses. They are often in charge of collecting or sorting products. For such robots, computation-intensive operations account for a significant per- centage of the total energy consumption and consequently affect battery life. Besides, in order to keep both the power con- sumption and hardware complexity low, simple micro-controllers or single-board computers are used as onboard local control units. This limits the computational capabilities of robots and consequently their performance. Offloading heavy computation to Cloud servers has been a widely used approach to solve this problem for cases where large amounts of sensor data such as real-time video feeds need to be analyzed. More recently, Fog and Edge computing are being leveraged for offloading tasks such as image processing and complex navigation algorithms involving non-linear mathematical operations. In this paper, we present a system architecture for offloading computationally expensive localization and mapping tasks to smart Edge gateways which use Fog services. We show how Edge computing brings computational capabilities of the Cloud to the robot environment without compromising operational reliability due to connection issues. Furthermore, we analyze the power consumption of a prototype robot vehicle in different modes and show how battery life can be significantly improved by moving the processing of data to the Edge layer

Offloading SLAM for Indoor Mobile Robots with Edge, Fog, Cloud Computing

Indoor mobile robots are widely used in industrial environments such as large logistic warehouses. They are often in charge of collecting or sorting products. For such robots, computation-intensive operations account for a significant per- centage of the total energy consumption and consequently affect battery life. Besides, in order to keep both the power con- sumption and hardware complexity low, simple micro-controllers or single-board computers are used as onboard local control units. This limits the computational capabilities of robots and consequently their performance. Offloading heavy computation to Cloud servers has been a widely used approach to solve this problem for cases where large amounts of sensor data such as real-time video feeds need to be analyzed. More recently, Fog and Edge computing are being leveraged for offloading tasks such as image processing and complex navigation algorithms involving non-linear mathematical operations. In this paper, we present a system architecture for offloading computationally expensive localization and mapping tasks to smart Edge gateways which use Fog services. We show how Edge computing brings computational capabilities of the Cloud to the robot environment without compromising operational reliability due to connection issues. Furthermore, we analyze the power consumption of a prototype robot vehicle in different modes and show how battery life can be significantly improved by moving the processing of data to the Edge layer

Hydrogen absorption properties of amorphous (Ni0.6Nb0.4−yTay)100−xZrx membranes

Ni based amorphous materials have great potential as hydrogen purification membranes. In the present work the melt spun (Ni0.6Nb0.4−yTay)100−xZrx with y=0, 0.1 and x=20, 30 was studied. The result of X-ray diffraction spectra of the ribbons showed an amorphous nature of the alloys. Heating these ribbons below T < 400 °C, even in a hydrogen atmosphere (1−10 bar), the amorphous structure was retained. The crystallization process was characterized by differential thermal analysis and the activation energy of such process was obtained. The hydrogen absorption properties of the samples in their amorphous state were studied by the volumetric method, and the results showed that the addition of Ta did not significantly influence the absorption properties, a clear change of the hydrogen solubility was observed with the variation of the Zr content. The values of the hydrogenation enthalpy changed from ~37 kJ/mol for x=30 to ~9 kJ/mol for x=20. The analysis of the volumetric data provides the indications about the hydrogen occupation sites during hydrogenation, suggesting that at the beginning of the absorption process the deepest energy levels are occupied, while only shallower energy levels are available at higher hydrogen content, with the available interstitial sites forming a continuum of energy levels

Determining the impacts of environmental parameters on model microbial community dynamics isolated from Rustumihia WWTP/Iraq

The composition of Rustumihia microbial community and their diversity with oxylene-contaminants were investigated by applying molecular techniques - polymerase chain reaction and denaturing gradient gel electrophoresis (PCR and DGGE) - via investigating 16S rRNA gene fragments and understand the interrelationships between microbial community composition and structure for established microbial model community isolated from Rustumihia WWTP. To this end, the established consortium could be used to assess the microbial response as defined by diversity and richness shifts, which are linked to changes in growth conditions. In this research paper a synthetic consortium was created by isolating indigenous microbial community members from the Rustumihia WWTP and subjecting the consortium to different pH conditions (6.5, 7.0 and 7.5), o-xylene concentrations (0.5, 5 and 50 Mm) and temperatures (25°C, 35°C, 45°C and 55°C). The results of this study indicated that the high o-xylene concentration of 50 mM was tolerated and degraded effectively at 35°C and 55°C, and pH 6.5 (P < 0.001). Bacterial richness and diversity were recorded according to the Hill parameters of 0D, 1D and 2D under each of the growth conditions, and then linked to the o-xylene degradation efficiency. At 35°C and pH 6.5, the consortium achieved high degradation percentage for each of 0.5, 5 and 50 mM of o-xylene with values of 73.1%, 94.8% and 63.08%, respectively. The current study is the first of its kind in Iraq. It investigates the enrichment, isolation, and identification of a microbial community from the Rustumihia WWTP and determines the efficiency of the isolates to tolerate and degrade oxylene, highlighting their sole source of hydrocarbon. This research underscores the usefulness of molecular techniques for both diversity and richness to understand the ecological impact of o-xylene as a contaminant and to identify potential molecular techniques for detection of gene that is responsible for o-xylene degradation

EV Hosting Capacity Enhancement in a Community Microgrid Through Dynamic Price Optimization-Based Demand Response

Community microgrids, as an emerging technology, offer resiliency in operation for smart grids. Microgrids are seeing an increased penetration of eco-friendly electric vehicles (EVs) in recent years. However, the uncontrolled charging of EVs can easily overwhelm such electric networks. In this work, we propose an efficient demand response (DR) scheme based on dynamic pricing to enhance the capacity of the microgrid to securely host a large number of EVs. A hierarchical two-level optimization framework is introduced to realize the DR scheme. At the upper level, the dynamic prices for the participating users in DR are optimized while at the lower level, each user optimizes its energy consumption based on the price signal from the upper level. An evolutionary algorithm and a mixed-integer linear programming model is employed to solve the upper and lower level problems, respectively. Energy scheduling problems of the users are solved in a distributed manner which adds to the scalability of the approach. The proposed DR scheme is tested on a microgrid system adopted from the IEEE European low-voltage distribution network. Numerical experiments confirm the effectiveness of the proposed DR scheme compared to the benchmark pricing policies from the literature

A review of the alumina recovery from coal fly ash, with a focus in China

Coal fly ash, an industrial by-product, is derived from coal combustion in thermal power plants. It is one of the most complex and abundant of anthropogenic materials and its improper disposal has become an environmental concern and resulted in a waste of recoverable resources. Coal fly ash is rich in alumina making it a potential substitute for bauxite. With the diminishing reserves of bauxite resources as well as the increasing demand for alumina, recovering alumina from fly ash has attracted extensive attentions. The present review first describes the alumina recovery history and technologies, and then focuses on the recovery status in China. Finally, the current status of fly ash recycling and directions for future research are considered

Characterisation of indigenous microbial community isolated from wastewater treatment phases Baghdad/Iraq

Biodegradation processes could be efficient for such organic contaminants like o-xylene within sewage. Since the biodegradation processes is mainly controlled by microbial communities therefore, this research paper intended that the bioaugmentation process application might speed up or improve biodegradation process in Rustumihia plant. It delivers an initial knowledge of the effects of one of the most complicated organic contaminants at Rustumihia plant. In addition to that, it suggested the using of indigenous microbial communities that is isolated from the treatment plant within the application of bioaugmentation. It reveals findings on the ecology of o-xylene degradation via using bacterial communities that were already enriched and isolated from the four important treatment phases of Iraq's Rustumihia plant

Climate change-driven losses in ecosystem services of coastal wetlands: A case study in the West coast of Bangladesh

© 2018 The Authors Climate change is globally recognized as one of the key drivers of degradation of coastal wetland ecosystems, causing considerable alteration of services provided by these habitats. Quantifying the physical impacts of climate change on these services is therefore of utmost importance. Yet, practical work in this field is fragmented and scarce in current literature, especially in developing countries which are likely to suffer most from the adverse climate change impacts. Using a coherent scenario-based approach that combines assessment of physical impacts with economic valuation techniques, here we quantify potential climate change driven losses in the value of wetland ecosystems services due to relative sea-level rise (RSLR)-induced inundation in the vulnerable Western coastal area of Bangladesh in 2100. The results show a small inundation area in 2100 under the three IPCC climate scenarios of RCP2.6 (with 0.25 m of RSLR), RCP6.0 (with 1.18 m of RSLR), and RCP8.5 (with 1.77 m of RSLR) for the coastal wetland ecosystems including the Sundarbans mangrove forest, neritic system and aquaculture ponds. In all scenarios, RSLR will drive a loss in the total value of ecosystem services such as provision of raw materials, and food provision, ranging from US$0–1 million to US$ 16.5–20 million, respectively. The outcomes of this study reveal that RSLR-induced inundation on its own, is unlikely to be a major threat to the wetland ecosystems in Western coast of Bangladesh. This would suggest that other climate change impacts such as coastal erosion, increase in frequency of cyclone events, and sea temperature rise might be the likely primary drivers of change in the value of wetland ecosystems services in this area