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Smart agriculture is an enabling technology addressing the increasing challenges of efficiency, sustainability, and quality of food production. It requires rich data from the farming area at high spatial and temporal resolution. Although remote sensing systems have become readily available recently, in-situ sensing is still required to capture important properties of soil, crops, and their close environment. Ubiquitous sensor networks (USNs) provide a seamless and real-time in-situ sensing infrastructure that could overcome some limitations of smart agriculture. Resource efficiency is essential for USNs due to 1) the expected long operation time in typically resource-constrained environments, 2) the vast amount of captured and processed data, and 3) the ever-increasing application requirements. This survey comprehensively analyzes resource optimization techniques for USNs along three USN layers: the sensing, the communication & connectivity, and the processing & analysis layer. It discusses the application of these techniques in the smart agriculture domain and identifies current challenges and open research issues.

With the ageing of society, the number of households with older individuals or couples living alone is increasing. An "ageing-in-place" approach allows older adults to continue to live at home and receive help only when needed. However, this approach is insufficient for emergencies, such as falls, as well as for individuals with gradually deteriorating health conditions, such as frailty. Unexpected accidents significantly reduce the quality of life (QoL) of older adults. This paper proposes a new framework, the mobility ubiquitous sensor edge environment (MUS3E), to digitally transform ordinary houses to detect the movement of older individuals throughout their home environment and to notify family members and care providers of residents' health status and safety information. The framework can be easily and inexpensively installed in any home, transforming an ordinary house into a smart home with an automated function for monitoring older residents. It uses ambient sensors such as passive infrared ray sensors to automatically measure health conditions by measuring factors such as walking speed. Residents need not interact with or control the system and can go about their daily lives. Since the sensors used in this system are mass-produced consumer products, they are inexpensive and easily replaceable, as there are many alternatives. In this study, we were able to demonstrate the practically and feasibility of this framework using a prototype that uses open architecture Internet of Things (IoT) software (Debian GNU/Linux 11, Arduino 1.8.19, ESP8266 2.7.4, ESP32 1.0.6, PubSubClient 2.8.0, ESPPerfectTime 0.3.0, mosquitto 2.0.11) components to digitally transform the living environment of older individuals. [ABSTRACT FROM AUTHOR]

A digitally enabled environment is a setting which incorporates sensors coupled with reporting and analytics tools for understanding, observing or managing that environment. Large scale data collection and analysis are a part of the emerging digitally enabled approach for the characterisation and understanding of our environment. It is recognised as offering an effective methodology for addressing a range of complex and interrelated social, economic and environmental concerns. The development and construction of the approach requires advances in analytics control linked with a clear definition of the issues pertaining to the interaction between elements of these systems. This paper presents an analysis of selected issues in the field of analytics control. It also discusses areas of progress, and areas in need of further investigation as sensing networks evolve. Three case studies are described to illustrate these points. The first is a physical analytics test kit developed as a part of the “Reinvent the Toilet Challenge” (RTTC) for process control in a range of environments. The second case study is the Cranfield Urban Observatory that builds on elements of the RTTC and is designed to allow users to develop user interfaces to monitor, characterise and compare a variety of environmental and infrastructure systems plus behaviours (e.g., water distribution, power grids). The third is the Data and Analytics Facility for National Infrastructure, a cloud-based high-performance computing cluster, developed to receive, store and present such data to advanced analytical and visualisation tools.

Urban 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

A Smart City is an urban area that uses the Internet of things (IoT) sensors to collect data and information to enhance the operational aptitude, in a way to manage assets and resources efficiently. Smart governance is a factor of a smart city for intelligent utilization of ICT to enhance the basic leadership. The smart government may be considered as a reason for creating smart governance, through the application of rising information and communication technology for administering. Smart Governance is totally dependent on the information that is being recorderded. Smart consists of multiple factors that an essential role in smart city activities, which require complex collaborations between governments, citizens and different partners. In this article, a new computational method is proposed for the evaluation of the Governance factors of the smart city using Hierarchical Mamdani Type-1 Fuzzy Expert System and empowered with fuzzy based data ingestion techniques.

A Smart City is an urban area that uses the Internet of things (IoT) sensors to collect data and information to enhance the operational aptitude, in a way to manage assets and resources efficiently. Smart governance is a factor of a smart city for intelligent utilization of ICT to enhance the basic leadership. The smart government may be considered as a reason for creating smart governance, through the application of rising information and communication technology for administering. Smart Governance is totally dependent on the information that is being recorderded. Smart consists of multiple factors that an essential role in smart city activities, which require complex collaborations between governments, citizens and different partners. In this article, a new computational method is proposed for the evaluation of the Governance factors of the smart city using Hierarchical Mamdani Type-1 Fuzzy Expert System and empowered with fuzzy based data ingestion techniques. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a method on the tradeoff between packet transmission speed and battery life in wireless sensor networks (WSN). The data obtained by sensor nodes comprised various types of information with various levels of importance. A misjudgment of the priority of packets according to the importance of data may delay the transmission of important information. The energy consumed by sensor nodes varies according to system states. Therefore, this research used queuing theory and the birth-death process to build a mathematical model capable of quantifying various energy consumption parameters. MATLAB was used to calculate the distribution of system state probability for sensor nodes with two queues. Packet delay equation was then applied to obtain the expected values of delay time for packets of various priorities. We adjust various system parameters and observe how these changes influenced system state probability. Finally, we use different N values to obtain the minimal value of system energy consumption. Obtaining this value helps to overcome the energy hole problem (EHP), which in turn extends the lifespan of the overall WSN. Prioritizing packets can ensure the transmission of important data within a shorter time span. Experimental results show the energy consumption is reduced and important data can be transmitted with less packet delay time.

Ongoing Sensor Web developments make a growing amount of heterogeneous sensor data available to smart devices. This is generating an increasing demand for homogeneous mechanisms to access, publish and share real-world information. This paper discusses, first, an architectural solution based on Next Generation Networks: a pilot Telco Ubiquitous Sensor Network (USN) Platform that embeds several OGC® Sensor Web services. This platform has already been deployed in large scale projects. Second, the USN-Platform is extended to explore a first approach to Semantic Sensor Web principles and technologies, so that smart devices can access Sensor Web data, allowing them also to share richer (semantically interpreted) information. An experimental scenario is presented: a smart car that consumes and produces real-world information which is integrated into the Semantic Sensor Web through a Telco USN-Platform. Performance tests revealed that observation publishing times with our experimental system were well within limits compatible with the adequate operation of smart safety assistance systems in vehicles. On the other hand, response times for complex queries on large repositories may be inappropriate for rapid reaction needs.

Nowadays more advanced sensor networks in various fields are developed. There are lots of online sensors spreading around the world. Sensor networks have been used in Geospatial Information Systems (GIS) since sensor networks have expanded. Health monitoring, environmental monitoring, traffic monitoring, etc, are the examples of its applications in Geomatics. Sensor network is an infrastructure comprised of sensing (measuring), computing, and communication elements that gives an administrator the ability to instrument, observe, and react to events and phenomena in a specified environment. This paper describes about development boards which can be used in sensor networks and their applications in Geomatics and their role in wireless sensor networks and also a comparison between various types of boards. Boards that are discussed in this paper are Arduino, Raspberry Pi, Beagle board, Cubieboard. The Boards because of their great potential are also known as single board computers. This paper is organized in four phases: First, Reviewing on ubiquitous computing and sensor networks. Second, introducing of some electrical boards. Then, defining some criterions for comparison. Finally, comparing the Ubiquitous boards. [ABSTRACT FROM AUTHOR]

Ongoing Sensor Web developments make a growing amount of heterogeneous sensor data available to smart devices. This is generating an increasing demand for homogeneous mechanisms to access, publish and share real-world information. This paper discusses, first, an architectural solution based on Next Generation Networks: a pilot Telco Ubiquitous Sensor Network (USN) Platform that embeds several OGC® Sensor Web services. This platform has already been deployed in large scale projects. Second, the USN-Platform is extended to explore a first approach to Semantic Sensor Web principles and technologies, so that smart devices can access Sensor Web data, allowing them also to share richer (semantically interpreted) information. An experimental scenario is presented: a smart car that consumes and produces real-world information which is integrated into the Semantic Sensor Web through a Telco USN-Platform. Performance tests revealed that observation publishing times with our experimental system were well within limits compatible with the adequate operation of smart safety assistance systems in vehicles. On the other hand, response times for complex queries on large repositories may be inappropriate for rapid reaction needs. [ABSTRACT FROM AUTHOR]

Building energy management systems (BEMS) have commonly been applied to minimise building operation costs through effective building management. Our approach was to find a new method by which building information could be applied to ubiquitous sensor networks. A new BEMS framework to minimise energy consumption in building facility management and utilise energy optimally was devised. A sensor location model was constructed based on the concept of defining the minimum activity area dependent on furniture boundaries. Semantic location of the usable area relative to architectural components was first introduced to deliver high-level context to the sensing environment. A Gong-BEMS solution has been developed to demonstrate how spatial information can be constructed and exploited in the building energy management process. [ABSTRACT FROM AUTHOR]