Alberto Bonastre

Monitoring Pest Insect Traps by Means of Low-Power Image Sensor Technologies

Monitoring pest insect populations is currently a key issue in agriculture and forestry protection. At the farm level, human operators typically must perform periodical surveys of the traps disseminated through the field. This is a labor-, time- and cost-consuming activity, in particular for large plantations or large forestry areas, so it would be of great advantage to have an affordable system capable of doing this task automatically in an accurate and a more efficient way. This paper proposes an autonomous monitoring system based on a low-cost image sensor that it is able to capture and send images of the trap contents to a remote control station with the periodicity demanded by the trapping application. Our autonomous monitoring system will be able to cover large areas with very low energy consumption. This issue would be the main key point in our study; since the operational live of the overall monitoring system should be extended to months of continuous operation without any kind of maintenance (i.e., battery replacement). The images delivered by image sensors would be time-stamped and processed in the control station to get the number of individuals found at each trap. All the information would be conveniently stored at the control station, and accessible via Internet by means of available network services at control station (WiFi, WiMax, 3G/4G, etc.).

A Wireless Sensor Network approach for distributed in-line chemical analysis of water.

In this work we propose the implementation of a distributed system based on a Wireless Sensor Network for the control of a chemical analysis system for fresh water. This implementation is presented by describing the nodes that form the distributed system, the communication system by wireless networks, control strategies, and so on. Nitrate, ammonium, and chloride are measured in-line using appropriate ion selective electrodes (ISEs), the results obtained being compared with those provided by the corresponding reference methods. Recovery analyses with ISEs and standard methods, study of interferences, and evaluation of major sensor features have also been carried out. The communication among the nodes that form the distributed system is implemented by means of the utilization of proprietary wireless networks, and secondary data transmission services (GSM or GPRS) provided by a mobile telephone operator. The information is processed, integrated and stored in a control center. These data can be retrieved--through the Internet--so as to know the real-time system status and its evolution.

Distributed expert systems as a new tool in analytical chemistry

Abstract This article emphasizes the growing importance of artificial intelligence in the automation of chemical analysis processes. Nevertheless, the authors predict that the use of centralized knowledge-based systems – though not still consolidated – will probably be replaced by distributed expert systems with their multiple advantages (discussed in the article). Distributed expert systems, which are based on the utilization of highly intelligent analytical instrumentation connected by means of communication networks, permit the implementation of highly flexible control systems that are capable of adapting themselves to different situations. At the same time, it is possible to take advantage of the power offered by the new communication technologies in the field of analytical chemistry. Distributed expert systems are thoroughly described and illustrated with a detailed example of an application to the monitoring and control of an alcoholic fermentation process by means of on-line/in-line chemical analysis; this can be extended to any other process whose chemical parameters undergo variations in the course of time.

Historical Building Monitoring Using an Energy-Efficient Scalable Wireless Sensor Network Architecture

We present a set of novel low power wireless sensor nodes designed for monitoring wooden masterpieces and historical buildings, in order to perform an early detection of pests. Although our previous star-based system configuration has been in operation for more than 13 years, it does not scale well for sensorization of large buildings or when deploying hundreds of nodes. In this paper we demonstrate the feasibility of a cluster-based dynamic-tree hierarchical Wireless Sensor Network (WSN) architecture where realistic assumptions of radio frequency data transmission are applied to cluster construction, and a mix of heterogeneous nodes are used to minimize economic cost of the whole system and maximize power saving of the leaf nodes. Simulation results show that the specialization of a fraction of the nodes by providing better antennas and some energy harvesting techniques can dramatically extend the life of the entire WSN and reduce the cost of the whole system. A demonstration of the proposed architecture with a new routing protocol and applied to termite pest detection has been implemented on a set of new nodes and should last for about 10 years, but it provides better scalability, reliability and deployment properties.

An expert system as a tool for the specification and intelligent control of a flow injection analysis system

Abstract An expert system was designed with the intention that it should fully control a fermentation process, whose on-line monitoring is based on the determination of total acidity, reducing sugars, ethanol and pH all along the process. The expert system is then in charge of deciding when and which measurements are to be carried out according to the previously obtained results and a pre-determined set of rules. Additionally, the expert system is able to take decisions concerning possible malfunctions.

Rule nets: application to the advanced automation of a flow-injection analysis system

Abstract An expert system based on rule nets has been developed. This new tool—the rule net—consists of a set of conditional-type propositions which are mutually bound. In this work, a set of rule nets has been implemented by means of a self-developed pack called AUTOMAT. Time has been incorporated into the reasoning of the expert system in such a way that it is able to carry out the on-line monitoring of an alcoholic fermentation process.

A New Energy-Efficient, Scalable and Robust Architecture for Wireless Sensor Networks

The major problem for most of wireless sensor networks applications is the energy consumption. In this paper we propose a new architecture called EDETA (Energy-efficient aDaptive hiErarchical and robusT Architecture) optimized to save nodes power. This architecture is scalable and suitable for heterogeneous and homogeneous wireless sensor networks, supports single or multiple sinks, and also provides features increasely-demanded in the current applications such as fault tolerance and bounded-time response communications. The proposed protocol is able to autoconfigure, and it is based on two-levels hierarchical architecture. The lower level is based on cluster organization, while the upper one is formed as a dynamic tree of clusters heads to send the data to the sink. Our experiments, based on real energy measures, show that EDETA can reduce the energy consumption in typical applications in a factor of 8x compared with most popular power-aware protocols. Furthermore, EDETA multiplies the lifetime of the sensor network while providing, in addition, extra-features such as fault-tolerant mechanisms and bounded time.

Application of Wireless Sensor Network to Direct Load Control in Residential Areas

This paper describes the application of wireless sensor network to monitor and control electrical loads in residential areas, mainly heating and cooling loads, which accounts for around 50% of the residential electricity consumption. In this way, a control algorithm has also been implemented in order to select the optimum load control strategy according to a target demand profile and a set of prefixed constraints, allowing the customers to modify their power demand with minimum comfort levels. Therefore, this application offers the residential customers a flexible, powerful and low-cost tool to manage their electrical loads, avoiding any additional wiring and extending the wireless sensor network technology to small customers, with around 30% share of the global electricity consumption. This system has been implemented in a university environment, and the results are also included in this paper.

Monitoring of a wort fermentation process by means of a distributed expert system

Abstract A distributed expert system has been proposed for the monitoring of a wort fermentation process through the flow injection determination of total acidity, reducing sugars, ethanol and pH. Its configuration is mainly based on the use of distributed nodes connected by means of a network and is capable of adapting itself to different situations. Satisfactory results have been obtained when it has been applied in a brewery plant, important advantages being shown over previously implemented centralized knowledge-based systems.

Development and Assessment of a Wireless Sensor and Actuator Network for Heating and Cooling Loads

This paper describes a wireless sensor-actuator network to monitor and manage thermostatically controlled loads, mainly heating and cooling loads, which accounts for around 50% of the residential electricity consumption. A decentralized system is proposed to modify the electrical power demand according to a target demand profile and a set of prefixed constraints, maintaining minimum comfort levels and minimizing the infrastructure requirements. This solution offers the residential customers a flexible, powerful and low-cost tool to modify their power demand profile, avoiding any additional wiring and extending the wireless sensor-actuator networks technology towards small customers, with around 30% share of the global electricity consumption. The proposed system has been implemented and assessed in a university environment, where heating and cooling loads have been monitored and controlled. Acquired data are also included in this paper as well as an example of the forced switching-off time periods applied on the controlled loads, leading to approximately 15% reduction of the peak power demand.