Standard Interface Research Articles

Advanced Cu/Polymer Hybrid Bonding System for Fine‐Pitch 3D Stacking Devices

Hybrid bonding enables the commercialization of ultra‐fine pitch high‐density 3D packages. Cu/SiO2 hybrid bonding is the standard packing interface recently introduced in the industry. Herein, the Cu/polymer hybrid bonding interface beyond Cu/SiO2 is proposed in order to have high compatibility for additional processes in the future. Ideally, polymers can provide excellent bonding strength and low permittivity, enabling high‐speed signal transmission with high reliability. To realize it, optimum polymer and additives selection and polymer bonding processing development are needed to get the desired packaging interface. Therefore, detailed materials and processing challenges are discussed to realize the successful Cu/polymer hybrid bonding. Then, the authors’ preliminary results are suggested to supplement the feasibility of the emerging bonding technology.

Space vehicle docking system standardization

The International Docking System Standard (IDSS) was developed and establish to aid on-orbit crew rescue and joint operations between different spacecraft. For the International Space Station (ISS), the IDSS has successfully enabled Global interoperability for Commercial Crew and it is now being extended to the Artemis campaign. Similarly, as more companies, agencies, and nations announce their intentions to explore and occupy Low Earth Orbit (LEO) and Cis-Lunar space, including the Lunar surface, it is a natural supposition that new, vehicle interface standards will be required to support the build-up of infrastructure for campaign-based exploration or permanent occupation by national and multi-national Agencies, Industries, and Companies.A surface version of the IDSS, a.k.a. IDSS-Surface (IDSS-S), is under consideration at the NASA Johnson Space Center (JSC) by the docking discipline leads responsible for the leadership of technical development and negotiation of the original IDSS over a decade ago. The IDSS-S, like its predecessor, will ultimately detail the physical geometric mating interface and design load requirements to ensure physical interoperability and to support a broad set of design reference missions which, if accommodated, increases the probability of successful Lunar surface docking between different modules enabling the accessibility and inclusivity required for multi-national, sustainable Lunar exploration.

A Comprehensive Security Architecture for Information Management throughout the Lifecycle of IoT Products

The Internet of things (IoT) is expected to have an impact on business and the world at large in a way comparable to the Internet itself. An IoT product is a physical product with an associated virtual counterpart connected to the internet with computational as well as communication capabilities. The possibility to collect information from internet-connected products and sensors gives unprecedented possibilities to improve and optimize product use and maintenance. Virtual counterpart and digital twin (DT) concepts have been proposed as a solution for providing the necessary information management throughout the whole product lifecycle, which we here call product lifecycle information management (PLIM). Security in these systems is imperative due to the multiple ways in which opponents can attack the system during the whole lifecycle of an IoT product. To address this need, the current study proposes a security architecture for the IoT, taking into particular consideration the requirements of PLIM. The security architecture has been designed for the Open Messaging Interface (O-MI) and Open Data Format (O-DF) standards for the IoT and product lifecycle management (PLM) but it is also applicable to other IoT and PLIM architectures. The proposed security architecture is capable of hindering unauthorized access to information and restricts access levels based on user roles and permissions. Based on our findings, the proposed security architecture is the first security model for PLIM to integrate and coordinate the IoT ecosystem, by dividing the security approaches into two domains: user client and product domain. The security architecture has been deployed in smart city use cases in three different European cities, Helsinki, Lyon, and Brussels, to validate the security metrics in the proposed approach. Our analysis shows that the proposed security architecture can easily integrate the security requirements of both clients and products providing solutions for them as demonstrated in the implemented use cases.

Modular lightweight robot system for aircraft production using a generic OPC UA skill concept

There is a continuing trend in the aircraft industry to automate production. In order to be able to react to shortages of skilled workers, high order fluctuations and machine breakdowns, cost-effective, mobile and flexible systems are required to support the workers. This paper focuses on the integration of existing skill-based engineering concepts into production using standard OPC Unified Architecture interface, where production systems can be built quickly by simply interconnecting modules. The interconnected modules together form higher level subsystems enabling reusability of the individual modules as well as the assembled subsystems across several use cases. The approach is evaluated on a production related mobile robot system, whose task is to drive to the workstation, reference the component and drill holes in a vertical tail plane section of an aircraft. All devices from different suppliers contain skill-based modules based on standards defined by OPC Foundation and communicate via OPC UA-based Client/Server communication.

XyGen: Synthetic data generator for feature selection

Given the large number of feature selection algorithms, it has become imperative to have a uniform procedure for evaluating the performance of the algorithms. We propose a library of synthetic datasets designed specifically to test the effectiveness of feature selection algorithms. The datasets are inspired by applications in the field of electronics and have a range of characteristics to provide a variety of test scenarios. The software comes in the form of a Python library with standard interface for loading and generating datasets. Each dataset is implemented as a function that allows control of various parameters of the data.

Vitruvius+: An Area-Efficient RISC-V Decoupled Vector Coprocessor for High Performance Computing Applications

The maturity level of RISC-V and the availability of domain-specific instruction set extensions, like vector processing, make RISC-V a good candidate for supporting the integration of specialized hardware in processor cores for the High Performance Computing (HPC) application domain. In this article, 1 we present Vitruvius+, the vector processing acceleration engine that represents the core of vector instruction execution in the HPC challenge that comes within the EuroHPC initiative. It implements the RISC-V vector extension (RVV) 0.7.1 and can be easily connected to a scalar core using the Open Vector Interface standard. Vitruvius+ natively supports long vectors: 256 double precision floating-point elements in a single vector register. It is composed of a set of identical vector pipelines (lanes), each containing a slice of the Vector Register File and functional units (one integer, one floating point). The vector instruction execution scheme is hybrid in-order/out-of-order and is supported by register renaming and arithmetic/memory instruction decoupling. On a stand-alone synthesis, Vitruvius+ reaches a maximum frequency of 1.4 GHz in typical conditions (TT/0.80V/25°C) using GlobalFoundries 22FDX FD-SOI. The silicon implementation has a total area of 1.3 mm 2 and maximum estimated power of ∼920 mW for one instance of Vitruvius+ equipped with eight vector lanes.

Versatile DMA Engine for High-Energy Physics Data Acquisition Implemented with High-Level Synthesis

FPGA-based cards for data concentration and readout are often used in data acquisition (DAQ) systems for high-energy physics experiments. The DMA engines implemented in FPGA enable efficient data transfer to the processing system’s memory. This paper presents a versatile DMA engine. It may be used in systems with FPGA-equipped PCIe boards hosted in a server and MPSoC-based systems with programmable logic connected directly to the AXI system bus. The core part of the engine is implemented in HLS to simplify further development and modifications. The design is modular and may be easily integrated with the user’s DAQ logic, assuming it delivers the data via a standard AXI-Stream interface. The engine and accompanying software are designed with flexibility in mind. They offer a simple single-packet mode for debugging and a high-performance multi-packet mode fully utilizing the computational power of the processing system. The number of used DAQ cards and the amount of memory used for the DMA buffer may be modified in the runtime without rebooting the system. That is particularly useful in the development and test setups. This paper also presents the development and testing methodology. The whole design is open-source and available in public repositories.

Design of a Standard and Programmatically Accessible Interface for Smart Meters to Allow Monitoring Automation of the Energy Consumed by the Execution of Computer Software

Software has become more computationally demanding nowadays, turning out high-performance software in many cases, implying higher energy and economic expenditure. Indeed, many studies have arisen within the IT community to mitigate the environmental impact of software. Collecting and measuring software’s power consumption has become an essential task. This paper proposes the design of a standard interface for any currently available smart meter, which is programmatically accessible from any software application and can collect consumption data transparently while a program is executed. This interface is structured into two layers. The former is a driver that provides an OS-level standard interface to the meter, while the latter is a proxy offering higher-level API for a concrete programming language. This design provides many benefits. It makes it possible to substitute the meter for a different device without affecting the proxy layer. It also allows the presence of multiple proxy implementations to offer a programmatic interface to the meter for several languages. A prototype of the proposed interface design has been implemented for a concrete smart meter and OS to demonstrate its feasibility. It has been tested with two experiments. Firstly, its correct functioning has been validated. Later, the prototype has been applied to monitor the execution of a high-performance program, a machine learning application to select the most relevant features of electroencephalogram data.

MAIN ASPECTS OF IMPLEMENTATION OF CHARGING STATIONS FOR ELECTRIC TRANSPORTS IN LOGISTICS

The paper analyzes and compares charging stations for small electric vehicles, including fast and slow boats, electric cars and their components. The analysis of charging modes of electric vehicles showed that four internationally standardized modes are used, three of which use alternating current with single-phase and three-phase switching and only one – direct current. When charging on direct current, the fastest charging is provided. There are three main options for connecting the electric vehicles to the charging station: by means of a special power cable; by means of a pantograph from bottom to top and from top to bottom; wirelesses connection. There are four standardized cases of connecting charging stations to electric vehicles. Three cases of cable connection can be used on alternating current, only the third case – on direct current, and the fourth case – when wirelessly charging an electric vehicle. A comparison of existing types of connectors for charging electric vehicles has shown that the standardized interface between the charging station and the electric vehicle remains one of the most acute problems.

Using A. I. for the generation of visual references in digital audio games from the perspective of sound design

The aim of this article is to examine the application of artificial intelligence in producing visual references during the development of a digital game. These references are a standard inclusion in Game Design Documents or Art Design Documents and are typically displayed as mood boards. In this article, we will discuss sound design and how artificial intelligence, mainly Bing utilizing Dall-E and Midjourney, can produce images that cater to the requirements of a particular game. One of the primary issues we will explore is the efficiency of using artificial intelligence in this creative process in terms of speed, accuracy, efficacy, creativity and how the resulting content compares with human-generated content. One objective is to examine how artificial intelligence can produce visual references that exemplify more detailed sound groups, such as ambiences or interactive sounds linked with specific in-game activities. These visual references will undergo testing within a digital game presently under development, thus achieving validation through real-world application. The game’s genre is an audio game with no standard graphics or interface, tailored to the needs of players with visual impairments. For that reason, generating visual references remains the sole approach to comprehending the actual game environment.

A Machine-Learning-based Surrogate Modeling Methodology for Submodel Integration in the Holistic Railway Digital Twin Platform

A holistic railway infrastructure digital twin (DT) platform is sophisticated and consists of a series of submodels (e.g., turnouts, tracks, vehicles, etc.) that are built through various methodologies and software. However, integrating these submodels into the DT platform is tremendously challenging due to considerable computational complexity, software and interface restrictions. To this end, we designed a machine learning (ML) based surrogate modeling methodology for the submodel integration in the holistic railway infrastructure DT platform and illustrated the methodology through a case study. In this case study, an ML-based surrogate model for multibody simulation of railway vehicle-track dynamics is created, which can replace the railway vehicle-track simulation executed with the Multibody Dynamics (MBD) Simulation commercial software SimPACK. The well-built ML model can accurately and quickly predict the vehicle-track system's dynamic responses to different track irregularities. Besides, the integration process of the ML-based surrogate model into the DT platform through a standardized open-source Functional Mock-up Interface (FMI) is also proposed. The developed surrogate modeling methodology shows great promise owing to its high fidelity, which is verified by the measurement data collected from the Austrian national railway track system. The main contribution of our work lies in the well-built ML-based surrogate modeling methodology for reducing the computation complexity and time of different submodels, which facilitates the unification and integration of different submodels. Furthermore, this approach can also be applied to other submodels and help to build the holistic railway DT platform collaboratively.

A Practical R&D Expenditure Statistic and Management Method Based on Spatial-Temporal Representation of Multi-factors and Data Twin Technology

Nowadays, R&D Expenditure plays an important role in more and more creative activities of enterprises and other entities, especially in research activities and programs of society. However there still have a big problem that is how to collect and classify R&D Expenditure accurately. In this paper, after analyzing the restrictive collection factors on R&D Expenditure statistically, a practical scheme was provided that including R&D Expenditure Feature Vector and “Object Wood” concept were defined firstly, intelligent receipt recognizing model (IRPM), intelligent receipt persona model (IRRM) based on spatial-temporal representation of multi-factors and R&D expenditure data Twin(REDT) based on data multi relationship were developed creatively. Besides, intelligence carrier-class R&D expenditure management system (REMS) was developed based on above novel technologies and deployed on cloud with SaaS mode. For calling advantageously and updating conveniently, API standard interface and Full Stack Security Mechanism were also improved and used in REMS. Meanwhile, it was proved that REMS had better performance on assisting enterprise in collecting and using their R&D Expenditure after REMS employed by 50 industrial enterprises at first batch in practical over a period of time. There also have better economic benefits and social benefits after REMS was used by 211 enterprises in practically. Next, REMS would be utilized and tested in more scope of important entities so that the correlation technologies could be tested, iterated and optimized forward in the future. Actually, REMS is becoming R&D Expenditure industrial promoted by investor and market. Eventually, REMS would become one of the best R&D Expenditure collecting and using tools, it would not only promote R&D Expenditure increase but also become a industrial correlating with R&D Expenditure.

Enhancing OAuth With Blockchain Technologies for Data Portability

To satisfy the requirement of data portability, current service providers (or resource servers) usually provide OAuth-based schemes for third party applications (or clients) to access user data with the users consent. To shoulder the costs of maintaining relationships with potential third party applications, a service provider may adopt delegate the task of authentication and authorization to an authorization server. However, current OAuth specification does not specify the interactions between an authorization server and a resource server. To address this limitation, this study proposes the MyDataChain framework to enhance the existing OAuth specification with blockchain technology. The proposed framework utilizes smart contracts to establish the standard interface to support the processes of authorization requesting, granting, and revocation. As blockchain technologies can ensure data integrity, the framework can use the data stored in the blockchain to resolve disputes among different parities. Moreover, as the proposed framework uses the Non-Interactive Zero-Knowledge (NIZK) scheme, the proposed framework can achieve its purpose without storing any personal identifiable or traceable data in the blockchain.

A secured big-data sharing platform for materials genome engineering: State-of-the-art, challenges and architecture

Materials are the foundation of social development. The vigorous development of big-data technology has brought new opportunities for material research and development, gradually entering the data-driven paradigm. How to safely collect, store and utilize material big-data to realize the design and prediction of advanced materials has essential research significance and value. Many material big-data platforms have been constructed to gather multi-source heterogeneous material data. However, these traditional platforms are hard to realize the safe and efficient circulation and utilization of data. Relying on the national Materials Genome Engineering (MGE) project, we built a secured big-data sharing platform and proposed corresponding data collection, storage, utilization, and security solutions. On the one hand, the blockchain framework working as a ‘middleware’ provides a standard application program interface for data interaction between participants, and participants do not need to perceive the underlying system framework; on the other hand, it provides a unified management and security mechanism for the platform. In terms of collection, the dynamic container model is used to solve the data normalization problem, thereby improving data quality. In terms of storage, data adaptors store normalized data in different databases for distributed storage and unified scheduling. The platform provides a unified service gateway to schedule all services for data utilization. The secured big-data sharing platform can improve data utilization, promote material data sharing, accelerate material discovery, and serve the data needs of high-throughput computing and the design of new materials.

Principles of processing and three-dimensional modelling through lidar data for applied research of the urban environment

Introduction. The 3D modeling technology of the urban environment using LiDAR survey data expands the possibilities of urban research. With proper use of various methods, models and algorithms for processing and analyzing LiDAR data, they can significantly facilitate and open up new opportunities for many applications discussed in this paper. The main research objective of the paper is to review methods for analyzing LiDAR survey data in urban studies and to present individual elements of the author’s optimization of these methods. Results. LiDAR data obtained as a result of laser scanning of the earth's surface from a certain vehicle form a three-dimensional terrain model in the point cloud form of varying density degrees. The post-processing of such data can branch out into many applications, which are discussed in this paper. The building extraction from a cloud of LiDAR points is performed using complex computational operations, the essence of which is to calculate the points of separate planes of the buildings roofs and then extract these points for 3D building modeling. There are many approaches to building extraction that aim to either improve the quality and accuracy of the extracted models or to speed up the data processing. Finding the optimal solution for 3D modeling of the urban environment is an urgent task in this area of research. Tracking changes in urban buildings involves comparing digital models of urban areas for different time periods in order to obtain the changes volume for each building. In a similar fashion, LiDAR data is used to assess damage to buildings by creating random points on the buildings walls and comparing their displacements before and after the damage. The population estimate using LiDAR data is based on a comparison of population data for census tracts with data on the number, area and volume of buildings in the same tracts obtained from processed LiDAR data. As a result, the expected population in each individual building can be calculated. Roads extraction from LiDAR data is performed by creating an image of the LiDAR laser pulse intensity and then comparing this image with a digital surface model. The article provides an example of a scheme for such road extraction. In addition, methods for extracting and mapping power lines by filtering the corresponding points are also considered. The ability to determine the exact size, slope, and exposure of a building's roof plane also makes it possible to estimate the potential level of solar radiation received by the roof, which can contribute to the optimal placement of solar power plants. Such an assessment may cause some difficulties, which are discussed in the article. The article proposes various optimization solutions for the considered methods, which were partially implemented in the ELiT software. In addition to effective tools for automatic data processing, the ELiT Project also provides an environment for high-quality visualization of results in a standard web-GIS interface. Conclusions. LiDAR data, in combination with efficient algorithms for processing and filtering data, greatly facilitates the solution of a number of tasks related to area monitoring and urban planning. In the future, the high accuracy of LiDAR data and the possibility of their visualization in GIS will make it possible to analyze the urban development features in order to identify the urban geosystemic properties of the city.

Altered Cellular Sedimentation during Apheresis Impacts Outcomes of Peripheral Blood Stem Cell Collection Efficiency in Patients with Sickle Cell Disease

Recent reports have demonstrated the potential for gene therapy as a therapeutic option to achieve a durable cure in patients with sickle cell disease (SCD). However, for these emerging cell therapies, relatively large numbers of peripheral blood hematopoietic stem cells (PB HSCs) are required to generate a therapeutic dose. Outcomes of stem cell collections in patients with SCD are highly variable, at times yielding far fewer numbers of HSCs in the product than predicted by the number of PB CD34+ cells. While the CXCR4 antagonist plerixafor has emerged as a safe and reliable drug to mobilize CD34+ cells in patients with SCD, collection failures continue to occur requiring additional cycles or failure to generate a gene therapy product. We sought to understand the mechanics affecting stem cell sedimentation in real time and posited that SCD disease associated changes to red cells results in altered HSC sedimentation during apheresis, negatively impacting collection. Methods Autologous PB stem cell collections were performed in patients with SCD following mobilization with 240ug/kg plerixafor. To uncover the mechanisms impacting apheresis efficiency for collecting PB HSCs, we devised a method to interrogate the sedimentation of cells in peripheral blood in real time, by interrupting the return collection circuit line. Cellular composition analyses of the collecting interfaces were performed including CD34+ enumeration by flow cytometry, CBC and differential, reticulocyte counts, and surface CD47 expression of red blood cells (RBCs). Results Patients were mobilized with 240ug/kg of plerixafor up to 6 hours before apheresis collection. We collected fewer cells than predicted (3.78 million cells/kg) in these patients with an overall average apheresis collection efficiency of 38%, and a strikingly wide range of 2%-107%. We determined that the lower collection efficiency outcomes were primarily derived when using standard apheresis interface settings. The pre-apheresis PB CD34+ counts were less predictive of total CD34+ cells collected (p=0.012) in patients with SCD (r2=0.2557, p=0.0023) when compared to historical control patients without SCD (r2=0.7638, p<0.0001). Real time measurement of cell counts at standard (Hematocrit 3%, S) and deep (Hematocrit 5%, D) collecting interfaces of the apheresis machine showed a significant decrease in lymphocytes (p=0.0146), increase in monocytes (p=0.0496), and increase enrichment in CD34+ cells at the D interface (Panel A). Enrichment of CD34+ cells correlated with monocyte enrichment and (n=21, r2=0.6706, p<0.0001) and an increased fold change in CD34+ cells between the S and D interfaces correlated with higher PB reticulocyte percentage (r2=0.5295, p=0.0111). Further analysis of the individual collection interfaces revealed that most RBCs were HbS containing despite a PB HbS concentration <30%, consistent with an enrichment for shorter lived sickle red cells. CD47 expression has been previously reported in higher concentrations on the surface of younger RBCs during erythropoiesis. Surface expression of CD47 was found to be significantly higher at both the S and D interfaces compared to the PB of patients, indicating that the accumulation of a younger population of RBCs at the collecting interfaces. As microcytic RBCs have been associated with poor collection efficiencies, the SCD red cell hemoglobin concentration in the PB was used as a marker for size and a significant correlation was determined (r2=0.6086, p=0.0001). Patients with SCD can mobilize PB HSC in response to plerixafor but demonstrate specific characteristics that impede the collection of stem cells. During apheresis, CD34+ stem cells sediment at a deeper hematocrit interface in the buffy coat as a result of displacement by the younger patient-derived population of RBCs. The relative shift in erythrocyte sedimentation requires a corresponding alteration in collection strategies to improve the collection efficiency. In addition to red cell age, other factors that affect red cell buoyancy including iron status or additional globin gene mutations negatively impact apheresis stem cell collections. Full assessment of red cell parameters can identify patients that are at risk for poor stem cell collection outcomes. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Development of an Integrated Water Resource Scheduling Model Based on Platform Plug-In: A Case Study of the Wudu Diversion and Irrigation Area, China

Integrated water resource scheduling is a key strategy for controlling river floods as well as for promoting the benefits and abolishing the harmful aspects of water conservancy projects. It is necessary to explore an effective development mode to address the current issues of long development times and poor outcomes for integrated water resource scheduling models. Drawing on the concept of software reuse, a development mode for an integrated water resource scheduling model is offered based on “platform system + model plug-in”, the cores of which are plug-in modules and interface integration. The boundaries and connection relations of each plug-in module are formed based on the logical analysis of the model plug-in. A web application mode is used to implement a standardized interface, which can be quickly and seamlessly connected to the system platform. The model is explored and applied in the Wudu diversion and irrigation area in China. The generated model is eventually verified using data obtained from two flood periods. According to the simulation results, the gate operation will be convenient, and the target water level will be attained in the allocated time with a satisfactory peak-clipping effect. It shows both good coordination and great utilization value of the plug-in modules. The concept of designing a plug-in database is eventually taken into consideration for combining and generating an optimization model of each river.

The seeker R package: simplified fetching and processing of transcriptome data.

Transcriptome data have become invaluable for interrogating biological systems. Preparing a transcriptome dataset for analysis, particularly an RNA-seq dataset, entails multiple steps and software programs, each with its own command-line interface (CLI). Although these CLIs are powerful, they often require shell scripting for automation and parallelization, which can have a high learning curve, especially when the details of the CLIs vary from one tool to another. However, many individuals working with transcriptome data are already familiar with R due to the plethora and popularity of R-based tools for analyzing biological data. Thus, we developed an R package called seeker for simplified fetching and processing of RNA-seq and microarray data. Seeker is a wrapper around various existing tools, and provides a standard interface, simple parallelization, and detailed logging. Seeker's primary output-sample metadata and gene expression values based on Entrez or Ensembl Gene IDs-can be directly plugged into a differential expression analysis. To maximize reproducibility, seeker is available as a standalone R package and in a Docker image that includes all dependencies, both of which are accessible at https://seeker.hugheylab.org.

The FMI 3.0 Standard Interface for Clocked and Scheduled Simulations

This paper presents an overview and formalization of the Functional Mock-up Interface (FMI) 3.0. The formalization captures the new FMI 3.0 standard and is intended to be used as an introduction for conceptualizing the use of clocks in the FMI standard to support the simulation of event-based cyber-physical systems. The FMI 3.0 standard supports two kinds of clock-based simulations: Synchronous Clocked Simulation to ensure predictable systems scheduling with multiple simultaneous events and scheduled execution to facilitate real-time simulations comprising multiple black-box models by allowing fine-grained control over the computation time of submodels. The formalization is a basis for developing tools for orchestrating, verifying and validating the composition of multiple FMUs. The formalization is provided as an accessible VDM-SL specification.

CrowdPower: A Novel Crowdsensing-as-a-Service Platform for Real-Time Incident Reporting

Crowdsensing using mobile phones is a novel addition to the Internet of Things applications suite. However, there are many challenges related to crowdsensing, including (1) the ability to manage a large number of mobile users with varying devices’ capabilities; (2) recruiting reliable users available in the location of interest at the right time; (3) handling various sensory data collected with different requirements and at different frequencies and scales; (4) brokering the relationship between data collectors and consumers in an efficient and scalable manner; and (5) automatically generating intelligence reports after processing the collected sensory data. No comprehensive end-to-end crowdsensing platform has been proposed despite a few attempts to address these challenges. In this work, we aim at filling this gap by proposing and describing the practical implementation of an end-to-end crowdsensing-as-a-service system dubbed CrowdPower. Our platform offers a standard interface for the management and brokerage of sensory data, enabling the transformation of raw sensory data into valuable smart city intelligence. Our solution includes a model for selecting participants for sensing campaigns based on the reliability and quality of sensors on users’ devices, then subsequently analysing the quality of the data provided using a clustering approach to predict user reputation and identify outliers. The platform also has an elaborate administration web portal developed to manage and visualize sensing activities. In addition to the architecture, design, and implementation of the backend platform capabilities, we also explain the creation of CrowdPower’s sensing mobile application that enables data collectors and consumers to participate in various sensing activities.