Ubiquitous Sensor Network Research Articles

Energy conservation using PISAE and cross-layer-based opportunistic routing protocol (CORP) for wireless sensor network

In wireless sensor networks (WSNs) with constrained sensor node energy, data compression is crucial. Generally speaking, data communication uses up energy. By providing and receiving less data, a sensor node's lifespan is often increased. In this paper, provide an unique unsupervised neural network architecture called Partly-Informed Sparse Autoencoder (PISAE) that tries to reconstruct all sensor readings from chosen prime numbers. This architecture is used to implement the sensor selection approach that we propose. A key challenge for WSN is the selection of the cluster head (CH). Utilizing the K-Medoid, the clustering of sensor nodes is improved. The effect on quality of service (QoS), the location of the sensor nodes, the distance involved, and the energy status requirements are important factors. For the best choice of cluster heads in WSN with regard to distance and energy, the hybridization of two well-known optimization methods, namely Bacteria Foraging Optimization and Harmony Search Algorithm (HSA), is carried out in this study. Opportunistic routing protocol for WSN is proposed in the current work as a cross-layer based opportunistic Routing protocol (CORP). The suggested CORP approach is utilised to identify the best course of action to cut down on computation time and energy usage while enhancing data transmission dependability. Future generations of ubiquitous sensor networks won't have a single AI solution to the problems with energy and load. In addition, this study puts forth the idea of an energy-efficient routing using Fuzzy neural network (ERFN), which can increase the lifespan of WSNs by lowering energy consumption while maintaining energy usage balance. Based on the simulation findings, it can be stated that the proposed CORP approach increases QoS performance metrics such energy consumption, packet delivery rate, packet delay, network lifetime, throughput, and packet loss rate. The performance of the suggested method outperforms that of already-in-use algorithms like FRLDG, MOBFO-EER, and FEEC-IIR.

Precision Agriculture Using Soil Sensor Driven Machine Learning for Smart Strawberry Production.

Ubiquitous sensor networks collecting real-time data have been adopted in many industrial settings. This paper describes the second stage of an end-to-end system integrating modern hardware and software tools for precise monitoring and control of soil conditions. In the proposed framework, the data are collected by the sensor network distributed in the soil of a commercial strawberry farm to infer the ultimate physicochemical characteristics of the fruit at the point of harvest around the sensor locations. Empirical and statistical models are jointly investigated in the form of neural networks and Gaussian process regression models to predict the most significant physicochemical qualities of strawberry. Color, for instance, either by itself or when combined with the soluble solids content (sweetness), can be predicted within as little as 9% and 14% of their expected range of values, respectively. This level of accuracy will ultimately enable the implementation of the next phase in controlling the soil conditions where data-driven quality and resource-use trade-offs can be realized for sustainable and high-quality strawberry production.

Protic Ionic Liquid Electrolytes to Increase Areal Energy Density of RuO2 Micro-Supercapacitors

The rising growth of smart and autonomous microelectronic devices in the IoT (Internet of Things) era urges the development of advanced microscale energy sources with tailor-made features and customized energy/power requirements [1]. Micro-supercapacitors (MSCs) emerged as potential energy storage devices complementing micro-batteries to power ubiquitous sensor networks needed to foster the development of IoT. However, the low cell voltage and low energy density remain major bottleneck that prevents their application at a large scale in real devices. To mitigate this issue, several studies have been devoted to the engineering of MSC electrode materials and structural architecting of current collectors to enhance the surface area and areal energy density by considering the limited available footprint area [2]. This approach however has associated challenges such as complex synthesis route, the deleterious interfacial and mechanical stability of the electrode, and compatibility issues with the electrolyte and the current collector underneath [3]. Another important challenge to solve for reaching high energy density values in MSCs is the limited electrochemical stability window (ESW) of the electrolytes used as energy stored is directly related to the square of the cell voltage [4]. The electrolytes play a major role in deciding the ESW and liquid-state electrolytes currently employed are troublesome for the microfabrication process due to leakage, evaporation, and safety issues. Therefore, it’s imperative to develop alternative electrolytes including solid-state electrolytes reconcilable to the target application of MSCs. To address the low energy density challenge of current MSCs, we have developed interdigitated MSCs using hydrous ruthenium dioxide (RuO2) electrodes in combination with novel protic ionic liquid (PIL)-based electrolytes able to provide pseudocapacitance while affording a higher ESWs as compared to conventional aqueous electrolytes. As a state-of-the-art pseudocapacitive electrode material, RuO2 owns the key merits of excellent conductivity, high electrochemical reversibility, and cycling stability [5], whereas PILs could help alleviate issues facing currently used electrolytes such as evaporation and encapsulation problems pertaining to aqueous-based and flammability of common organic electrolytes [6], [7], [8]. In the next step, the slow proton transport kinetics of PILs were addressed by the doping of silicotungstic acid (SiWa, H4SiW12O40) with the PIL, which further boosted the pseudocapacitive current response with enlarged cell voltage. The real MSC device was realized by the use of RuO2 deposited on interdigitated porous Au current collectors having a high area enlargement factor (AEF) in combination with triethylammonium bis(trifluoromethanesulfonyl)imide (TEAH-TFSI)-based PIL. The resultant 3D MSC rendered a cell voltage exceeding 2V with areal capacitance as high as 86 mF cm-2 at 5 mV s-1 on par with the performance of 3D MSC tested using 0.5 M H2SO4 (cell voltage of 0.9 V and areal capacitance of 85 mF cm-2 at 5 mV s-1) but higher energy density performance (more than 4 times) using similar number of RuO2 deposition cycles. To demonstrate the potential integration in real on-chip device application, ionogel-based all-solid-state MSC is developed that showed performance comparable to liquid-state electrolyte with superior long-term cycling stability. This study gives a new perspective to develop all-solid-state micro-supercapacitors using pseudocapacitive active materials that can operate in ionic-liquid-based non-aqueous electrolytes compatible with on-chip IoT-based device applications seeking high areal energy/ power performance.

Communication Technologies in Emergency Situations

Emergency situations such as wildfires, water floods, or even terrorist attacks require continuous communication between the coordination centres, the several on-the-field teams, and their respective devices to properly address the adverse circumstances. From a technological point of view, this can be best seen as a live Ubiquitous Sensor Network—composed of human beings (e.g., first responders, victims) and devices (e.g., drones, environmental sensors, radios)—with stringent and special communication requirements in terms of flexibility, mobility, reliability, bandwidth, heterogeneity, and speed of deployment. However, for this specific use case, most of the already deployed and well-known communication technologies (e.g., satellite, 4G/5G) might become unusable and hard to repair due to the associated effects of the disaster itself. The purpose of this paper is (1) to review the emergency communications challenges, (2) to analyse the existing surveys on technologies for emergency situations, (3) to conduct a more updated, extensive, and systematic review of the emergency communications’ technologies, and (4) to propose a heterogeneous communication architecture able to communicate between moving agents in harsh conditions. The proposed approach is conceived to link the relocating agents that constitute a Ubiquitous Sensor Network spanning a large-scale area (i.e., hundreds of square kilometres) by combining Near Vertical Incidence Skywave technologies with Drone-Based Wireless Mesh Networks. The conclusions derived from this research aim to set up the fundamentals of a rapidly deployable Emergency Communications System inspired by the Ubiquitous Sensor Network paradigm.

Rate Control Optimization Algorithm of Ubiquitous Power Sensor Network Tester Based on Multimedia

With more and more video application scenarios and increasing complexity, the popularization of multimedia information and the urgent need to update wireless sensor networks have led to the emergence and development of wireless multimedia sensor networks. This paper focuses on the rate control optimization algorithm of multimedia-based ubiquitous power sensor network, which is mainly studied from three aspects: constructing algorithm verification platform based on multimedia technology, performance analysis, and optimization of rate control optimization algorithm based on multimedia technology. An algorithm verification platform is established based on multimedia technology. This article uses a scalable video coding method to design a client-driven scalable video transmission system. The simulation results show that the algorithm can effectively improve the video quality. The algorithm of rate control based on multimedia technology is proposed. A reliable multipath routing algorithm based on AODV is proposed. Based on the energy balance algorithm, the node-independent routing mechanism and link quality estimation model are introduced. An independent and reliable active/standby communication link to the node of the destination node is established. Linux, the full name of GNU/Linux, is a free-to-use and freely disseminated Unix-like operating system. It is a POSIX-based multiuser, multitasking, multithreaded, and multi-CPU operating system. With the development of the Internet, Linux has gained support from software enthusiasts, organizations, and companies all over the world. In addition to maintaining a strong momentum of development in servers, it has made considerable progress in personal computers and embedded systems. Under the Linux platform, a large number of tests are performed and the performance of the control code rate is analyzed. The so-called sensor network is a distributed intelligent network system that is composed of a large number of small sensor nodes with wireless communication and computing capabilities deployed in the active area through a self-organizing method that can autonomously complete designated tasks according to the environment. The distance between the nodes of the sensor network is very short, and the multihop wireless communication method is generally used for communication. The sensor network can run in an independent environment, or it can be connected to the Internet through a gateway so that users can access it remotely. It is concluded that ABR is the most suitable rate control algorithm for video transmission. According to the CQP experiment results, the QP value set in the improved ABR algorithm is at most 40; the security from the construction of the ubiquitous power sensor network to the final monitoring data collection and upload process is verified by simulating the hypothesis attacks and faults. It is proved that the construction of ubiquitous power sensor network can reduce the energy consumption and delay of monitoring data collection and verify the superiority of constructing ubiquitous power sensor network.

Intelligent Sound Monitoring and Identification System Combining Triboelectric Nanogenerator‐Based Self‐Powered Sensor with Deep Learning Technique

AbstractUrban sound management is required in a variety of fields such as transportation, security, water conservancy and construction, among others. Given the diverse array of available noise sensors and the widespread opportunity to connect these sensors via mobile broadband Internet access, many researchers are eager to apply sound‐sensor networks for urban sound management. Existing sensing networks typically consist of expensive information‐sensing devices, the cost and maintenance of which limit their large‐scale, ubiquitous deployment, thus narrowing their functional measurement range. Herein, an innovative, low‐cost, sound‐driven triboelectric nanogenerator (SDTENG)‐based self‐powered sensor is proposed, from which the SDTENG is primarily comprised of fluorinated ethylene propylene membranes, conductive fabrics, acrylic shells, and Kapton spacers. The SDTENG‐based sensor has been integrated with a deep learning technique in the present study to construct an intelligent sound monitoring and identification system, which is capable of recognizing a suite of common road and traffic sounds with high classification accuracies of 99% in most cases. The novel SDTENG‐based self‐powered sensor combined with deep learning technique demonstrates a tremendous application potential in urban sound management, which will show the excellent application prospects in the field of ubiquitous sensor networks.

SC-FDE Layer for Sensor Networks in Remote Areas Using NVIS Communications

Despite high costs and lengthy deployments, satellite communications have traditionally been used to provide coverage in remote areas. However, given the fact that there is no radio infrastructure available in these areas, Near Vertical Incidence Skywave (NVIS) technology has positioned itself as an attractive alternative to communicate with low-power nodes in remote areas. This type of communication works in the HF frequency range complying with STANAG and MIL-STD standards, which define a physical layer for scenarios that differ from NVIS and low-power communication. The purpose of this paper was to present the definition of a new communication physical layer based on single-carrier frequency-domain equalization (SC-FDE) based on these standards but adapted to the ionospheric communication channel. This physical layer was compared to an OFDM-based layer from a previous study. The experiments performed show that this new approach achieves better results than OFDM in terms of a higher signal quality with a higher specific BER probability. Finally, this layer was also used in the theoretical design of an NVIS gateway to link sensor network devices spanning large-scale remote areas in a secure manner in the context of ubiquitous sensor networks (USN).

Statistical Fault Analysis of the Simeck Lightweight Cipher in the Ubiquitous Sensor Networks

With the development of wireless technology, the ubiquitous sensor networks have a profound effect on the way human interacts with computers, devices and environment. In order to reduce the potentially serious risks in the interaction, applying lightweight ciphers is effective to balance security, efficiency and convenience. Simeck is such a lightweight cipher that provides data confidentiality, authentication and integrity. It is significant to explore whether Simeck remains robust security. Up to now, the attacking assumptions of the previous security analysis of Simeck focus on the known-plaintext attack and the chosen-plaintext attack. There is no literature about Simeck against the ciphertext-only attack, which represents the weakest attacking capability of the attackers. On the assumption of the ciphertext-only attack, this paper proposes the security analysis of Simeck against the statistical fault analysis with a series of novel distinguishers of KDE, MME and MME-GF. The experimental results show that the proposed distinguishers can recover the secret key of Simeck in both decreasing faults and increasing reliability and accuracy. Thus, Simeck cannot resist against the statistical fault analysis with the proposed distinguishers. Furthermore, the good performance of these novel distinguishers can be applied on the PRESENT lightweight cipher. It offers the valuable reference for the design and analysis of the lightweight ciphers in the ubiquitous sensor networks.

Energy‐Efficient Routing Using Fuzzy Neural Network in Wireless Sensor Networks

In wireless sensor networks, energy is a precious resource that should be utilized wisely to improve its life. Uneven distribution of load over sensor devices is also the reason for the depletion of energy that can cause interruptions in network operations as well. For the next generation’s ubiquitous sensor networks, a single artificial intelligence methodology is not able to resolve the issue of energy and load. Therefore, this paper proposes an energy‐efficient routing using a fuzzy neural network (ERFN) to minimize the energy consumption while fairly equalizing energy consumption among sensors thus as to prolong the lifetime of the WSN. The algorithm utilizes fuzzy logic and neural network concepts for the intelligent selection of cluster head (CH) that will precisely consume equal energy of the sensors. In this work, fuzzy rules, sets, and membership functions are developed to make decisions regarding next‐hop selection based on the total residual energy, link quality, and forward progress towards the sink. The developed algorithm ERFN proofs its efficiency as compared to the state‐of‐the‐art algorithms concerning the number of alive nodes, percentage of dead nodes, average energy decay, and standard deviation of residual energy.

Low-Cost Distributed Acoustic Sensor Network for Real-Time Urban Sound Monitoring

Continuous exposure to urban noise has been found to be one of the major threats to citizens’ health. In this regard, several organizations are devoting huge efforts to designing new in-field systems to identify the acoustic sources of these threats to protect those citizens at risk. Typically, these prototype systems are composed of expensive components that limit their large-scale deployment and thus reduce the scope of their measurements. This paper aims to present a highly scalable low-cost distributed infrastructure that features a ubiquitous acoustic sensor network to monitor urban sounds. It takes advantage of (1) low-cost microphones deployed in a redundant topology to improve their individual performance when identifying the sound source, (2) a deep-learning algorithm for sound recognition, (3) a distributed data-processing middleware to reach consensus on the sound identification, and (4) a custom planar antenna with an almost isotropic radiation pattern for the proper node communication. This enables practitioners to acoustically populate urban spaces and provide a reliable view of noises occurring in real time. The city of Barcelona (Spain) and the UrbanSound8K dataset have been selected to analytically validate the proposed approach. Results obtained in laboratory tests endorse the feasibility of this proposal.

NVIS Multicarrier Modulations for Remote-Sensor Applications.

The number of Internet of Things (IoT) devices has experienced a large growth during the last decade, as well as the data volume gathered from remote sensors. Satellites are still a suitable communication method and may be preferable for a remote ubiquitous sensor network (USN), which sometimes are located in places without much communications infrastructure where coverage is the principal drawback. Alternatively, the proposed solution for this article aims at a near-vertical incidence skywave (NVIS) channel for high frequencies (HF) with a low-cost platform, allowing a low-power transmissions coverage area up to 250 km for USN. The HF standards are focused on generic communication channels not being robust for NVIS communications. In this article we study and test an alternative based on orthogonal frequency-division multiplexing (OFDM) modulations to make them more robust and less dependent on the channel NVIS communications. For that purpose, we test the HF standard modulations and a designed OFDM modulation to prove the robustness of each. This study has been tested between Barcelona and Tarragona, using different transmission power levels and modulation orders.

Study of NVIS Channel for USN Protocol Definition in Antarctica

Every year, the number of ubiquitous sensor networks (USN) is increasing and the need for remote USN communications is emerging in some scenarios. As an alternative to satellite communications, more interests are focused on high frequencies (HF) communications as a low-cost option to reach links of more than 250 km without a line of sight. The HF standards are designed for generic communication channels being not robust for near vertical incidence skywave (NVIS) USN. In this article, we propose a new protocol for USN in remote places based on NVIS communications. For that purpose, we study the main characteristics of the NVIS channel with the presence of groundwaves, particularly in Antarctica. We analyze the availability of the channel, the height of the layers, the delay spread, and the Doppler spread. On the basis of the results obtained, we propose two protocols based on an OFDM (orthogonal frequency division multiplexing) modulation depending on the presence of the groundwave at the receiver. Finally, we make a simulation of the two OFDM configurations and we compare it with real tested standard modulations. The results show a better performance of the new protocol compared to the current HF standards.

PTSP Solution Strategy for Motion Trajectory of UAV in Ubiquitous Sensor Network

Abstract Nowadays, thanks to technological progress, the Unmanned Aerial Vehicles (UAVs) have appeared and allow to realize practical applications at lower costs with higher quality. These are widely used in the ubiquitous sensor networks USN. To improve their performance, it is interesting to plan their complex missions in reasonable solution times. In this paper we propose a modeling of the UAV motion in USN as being a Probabilistic Traveling Salesman Problem (PTSP), where the number of sensors to be served each time is a random variable. This method consists in optimizing the movement trajectory of the UAV in order to reduce the time for delivery of information to the users. This modeling makes it possible to recover the essential information of the system despite the disturbance of a subset of its elementary components, while ensuring the resolution of the addressed situation according to the a priori strategy of the PTSP. It ensures the existence of a solution adaptable to a multitude of TSPs in real time. We proposed numerical results based on exact Branch and Bound algorithm that provides an optimal solution through each set of sensors which occur with certain probabilities.

Fully Printed and Flexible Carbon Nanotube Transistors for Pressure Sensing in Automobile Tires

As the need for an increased supply and diversity of sensors expands, printed electronics have been identified as a promising approach for low-cost, ubiquitous sensor networks. In this paper, we demonstrate the use of a fully printed carbon nanotube thin-film transistor (CNT-TFT) for sensing environmental pressure over a pressure range extending from 0 to 42 PSIg. The transconductance of the CNT-TFT was found to be linearly correlated with environmental pressure at a sensitivity of 48.1 pS/PSI. We also demonstrate the capability of wirelessly transmitting the data measured by the pressure sensor using a simple Bluetooth module. Using the Bluetooth system, we observed the sensor’s response over time as pressure was dynamically changed. Finally, we packaged the sensor along with a material thickness sensor (developed in previous work) into a fully printed smart tire sensor system capable of mapping tire pressure and tread depth differentials.

A local algorithm to approximate the global clustering of streams generated in ubiquitous sensor networks

In ubiquitous streaming data sources, such as sensor networks, clustering nodes by the data they produce gives insights on the phenomenon being monitored. However, centralized algorithms force communication and storage requirements to grow unbounded. This article presents L2GClust, an algorithm to compute local clusterings at each node as an approximation of the global clustering. L2GClust performs local clustering of the sources based on the moving average of each node’s data over time: the moving average is approximated using memory-less statistics; clustering is based on the furthest-point algorithm applied to the centroids computed by the node’s direct neighbors. Evaluation is performed both on synthetic and real sensor data, using a state-of-the-art sensor network simulator and measuring sensitivity to network size, number of clusters, cluster overlapping, and communication incompleteness. A high level of agreement was found between local and global clusterings, with special emphasis on separability agreement, while an overall robustness to incomplete communications emerged. Communication reduction was also theoretically shown, with communication ratios empirically evaluated for large networks. L2GClust is able to keep a good approximation of the global clustering, using less communication than a centralized alternative, supporting the recommendation to use local algorithms for distributed clustering of streaming data sources.

From microwatt to gigabit: challenges of modern radio design

On the brink of introducing the fifth generation (5G) of cellular networks, the art of radio-frequency (RF) integrated circuit design has never seen such a wide spread of diverging requirements:On the one hand, ubiquitous sensor networks are mandating power budgets in the order of micro-watt. They should be constructed as energy-autonomous, wireless, low-cost sensor nodes. This demand is caused by massive deployment scenarios of billions of devices, which makes wires and batteries unpractical. As a result, the desire for the radio nodes to harvest their operational energy from the environment emerges.On the other hand, the recent and ongoing realization of gigabit-per-second capable cellular modems is driving hardware and power requirements to extremes. To overcome hardware limitations, introduced by analog impairments, digital correction and alignment algorithms are employed for compensation. These factors call for usage of expensive advanced CMOS technology nodes and increased utilization of digital signal processing techniques.In this paper, we recap ongoing trends and developments for ultra-low power and high-end transceiver (TRX) designs using CMOS technology nodes ranging from low-cost to highest performance.

Smart Cities in Taiwan: A Perspective on Big Data Applications

In this paper, we discuss the concept of a smart city based on information and communication technology (ICT), analyze the objectives of smart city development in Taiwan, and explain the supporting technologies that make such development possible. Subsequently, we propose a hierarchical structure framework of smart city systems with levels of complexity ranging from low to high and interconnections and interactive relationships in five dimensions: the Internet of Things (IoT), cloud computing, Big Data, Mobile Network, and smart business. We integrate each key resource of the core operation systems of cities to promote the innovative operation of cities and further optimize city development. We then propose a Big Data platform data flow framework that uses information from ubiquitous sensor networks and information equipment to analyze the Big Data application process of smart cities and determine the resulting advantages and challenges. Additionally, we analyze the current state of development of smart cities in Taiwan. Finally, we discuss a new philosophy of smart city development and provide a practical blueprint for the formation, operation, and development of the smart cities with the aim of creating a bright future for the smart cities of Taiwan.

Graphene/TiO2-Ag Based Composites Used as Sensitive Electrode Materials for Amaranth Electrochemical Detection and Degradation

Graphene/TiO2-Ag based composites having various quantities of TiO2-Ag nanoparticles (5, 10 or 15 wt%) were successfully prepared through a facile chemical-thermal route. The morphological and structural characteristics of the synthesized materials denoted GTA-5, GTA-10 and GTA-15 were investigated by TEM, XRD and FTIR techniques. The composites were used for the modification of three gold electrodes (Au/GTA-5, Au/GTA-10, Au/GTA-15) which were next employed in the electrochemical detection and degradation of amaranth (an azo dye model). The electrode with the best performance in terms of sensitivity was the Au/GTA-10 electrode. It had considerably larger sensitivity (24 mA/M), in comparison with that of Au/GTA-5 and Au/GTA-15 electrode (8 mA/M and 12 mA/M, respectively). The limit of detection was the same for all modified electrodes (LOD = 1 × 10−7 M; S/N = 3). The Au/GTA-10 electrode was also tested at the electrochemical degradation of amaranth, from aqueous solutions. The degradation reaction followed a first order kinetics with a half-time of degradation of 203 minutes. The response characteristics of the proposed sensor made it a good candidate for integration in the Ubiquitous sensor's network for IOT.

An Effective Sensor Cloud Control Scheme Based on a Two-Stage Game Approach

Motivated by complementing the ubiquitous sensor networks and cloud computing technique, a lot of attentions have been drawn to Sensor-Cloud (SC). The idea of SC thrives on the principle of virtualization of physical sensor nodes and has introduced the intermediate processing between physical sensor nodes and end users. This paper proposes an efficient interactive SC control scheme to provide on-demand sensing services for multiple applications. By adopting the game theory, we develop a new two-stage game model, which consists of a judicious mixture of selection and incentive algorithms. In our game model, a user can choose the most adaptable data center to execute its task, and each data center can give appropriate incentives to the participating sensors. The main merit possessed by our two-stage game approach is to shed light on the practical SC control problem while providing excellent adaptability and flexibility to satisfy the different application requirements. To the best of our knowledge, this is the first work to include a novel incentive algorithm in the SC system. Simulation results demonstrate that our approach can outperform existing schemes by about 5%~15% in terms of the normalized user profit, service delay, and SC system throughput. Finally, we discuss future directions for designing SC control frameworks including other issues.

Economic Analysis of USN-Based Data Acquisition Systems in Tall Building Construction

The successful construction of tall buildings requires effective construction management based on various quantitative data. The recent development of ubiquitous sensor networks (USNs) enables massive amounts of data to be collected in real-time. However, the application of USN-based data acquisition systems to repetitive tasks on typical floors of tall buildings can be inefficient, because this may involve the repetitive reinstallation of sensors and the repositioning of data loggers and routers to enable continuous data transfer. To minimize this cumbersome work, a modified data acquisition method using reusable sensor nodes and mobile devices can be a useful solution. This study analyzes the economic aspects of the USN-based systems for concrete temperature monitoring by using the activity-based costing technique. The case study shows that the modified system can reduce the process cost by about 19%. It can also reduce the resource input time of management by about 55%, freeing up time for other management activities. Moreover, the cost benefits should scale up as projects increasingly require more measurement and monitoring. This study should facilitate the application of USN-based information management systems, particularly for tall building construction.