This article presents a Wireless Sensor Network (WSN) system, developed to monitor concealed box‐shaped underground passages to protect wildlife. The system's purpose is to recognize the species of passengers (ie, human, canis, flying species, and so on) without using video sensors (image recognition) through data provided by sensors that measure distance and weight. Moreover, the information provided by the WSN was analyzed via a variety of methods, including a neural pattern recognition network, as well as clustering algorithms, which were able to recognize the species of passengers with certainty scores of over 90%. The main concern for future study is the evaluation of these passages, which are frequently located along main highways, and using data fusion to evaluate low‐cost and low‐power microsensors regarding their effectiveness, that is, whether they are frequently utilized by animals.

The advent of ICT services on water sector offers new perspective towards sustainable water management. This paper presents an innovative web-based platform, targeting primarily the household end-users. The platform enables consumers to monitor and control, on real-time basis, the water and energy consumption of their household providing valuable information and feedback. At the same time, the platform further supports end-users to modify and improve their consumption profile via an interactive educational process that comprises a variety of on-line tools and applications. This paper discusses the rationale, structure and technologies upon which the platform has been developed and presents an early prototype of the various tools, applications and facilities

Efficient water and energy use in water distribution systems is being limited by the lack of sufficient data about water and related energy consumption. Therefore, it is crucial to provide updated and continuous feedback information to water users. This paper describes relevant use cases to improve efficient water use and related energy consumption by water utilities and consumers through the use of smart metering technologies. A systematic approach was established to obtain a comprehensive list of possible functionalities, using the concept of use case. For the consumer domain, six high-level and 18 detailed-level use cases were obtained. For the water utility domain, seven high-level and 20 detailed-level use cases were described. The high-level use cases with higher priority to be implemented in the iWIDGET system were also identified based on the contribution of different target audiences. The list of use cases covers a comprehensive range of possible usages that can be built upon the exploitation of data related to water and energy use in water distribution systems and in households, which may be of further use as a guide for similar studies.

The implementation of decentralized water management (DWM) systems as a mainstream practice is impeded by the knowledge gaps on their actual performance in a range of development types and settings. On the other hand, wireless sensor networks (WSN) provide a capable platform for low cost, high performance and real-time monitoring. By bringing together the strengths of WSN technology and distributed, reactive, knowledge management and representation, implemented as a dual-layer ontology framework, this work provides a holistic approach to the management of DWM systems. Low-level real-time knowledge such as sensor observations (water consumption, water quality and soil quality) is represented directly in the ontology while high-level knowledge, e.g. about scheduling precision irrigation and about meeting grey water demand in the household, is inferred through low-level knowledge by means of rule-based reasoning. Ultimately, the proposed system aims to: control the grey water reuse process, detect and react to any failures and unusual events (e.g. floods, bursts, pump failures), analyze and improve the efficiency of water reuse, and predict the optimal time for maintenance, thus improving system availability.

Body sensor networks e.g., for health monitoring, consist of several low-power on-body wireless sensors, higher-level devices such as PDAs and possibly actuators such as drug delivery pumps. It is important that such networks can adapt autonomously to changing conditions such as failures, changes in context e.g., user activity, or changes in the clinical condition of patients. Potential reconfiguration actions include changing the monitoring thresholds on sensors, the analysis algorithms or the configuration of the network itself. This paper presents a policy-based approach for autonomous management of body-sensor networks using the concept of a Self- Managed Cell (SMC). Ponder2 is an implementation of this approach that permits the specification and enforcement of policies that facilitate management and adaptation of the response to changing conditions. A Tiny Policy Interpreter has also been developed in order to provide programmable decision- making capability for BSN nodes.

There is a lot of buzz regarding the automobile industry, and the dominant goal for car manufacturers is to enhance drivers' experiences. Engine optimization and alternative fuels have made progress toward their full potential; so the next step is creating self-driving vehicles. The first group to explore this idea was DARPA in the early 2000s. Since 2010, major technological advancements have been achieved. As crazy as it may sound, self-driving vehicles are being developed, and research funding has shifted toward this goal. The future is coming, and within the next decade, the first commercial prototypes are expected to be available for mass use.