This work presents the design and implementation of an IoT-based system that monitors the groundwater from the water table in a farming area in Argentina. Particularly, the system measures in real-time the fluctuations in the depth and quality of groundwater, and it represents a proof-of-concept led by the National Institute of Agriculture Technology (INTA). In this first stage, the system allows INTA to create a sandbox to both understand the behavior of groundwater and determine appropriate ways to deploy the monitoring system in semi-arid areas that produce crops. The management of soil water is mandatory to ensure the subsistence of life in the planet. It is particularly important in a climate change scenario, where water resources are becoming increasingly scarce. For that reason, several research projects are currently under development to understand the water table fluctuations, and based on it, to implement preparedness plans for particular areas. To the best of the authors knowledge, this is the first monitoring system of this kind that is being developed and deployed in the southern cone of Latin America. It is expected that the system allows farmers and government authorities to perform a more efficient soil water management and forecasting, reducing thus the uncertainty about the capability of particular areas to produce crops.

Measuring the water table level is a critical factor in irrigated agriculture in arid regions, as it can significantly influence the exchange of water and nutrients with crops. This work presents the design, implementation, and field validation of an open-source, solar-powered IoT device for autonomous groundwater level monitoring, combining long-range low-power LoRa communication, a non-contact pressure-based level sensor using the trapped-air capillary method, and an efficient power management stage that seamlessly switches between solar and battery power. Unlike existing commercial leveloggers, which are costly and lack integrated wireless telemetry and solar-based autonomy, the proposed platform is presented as a fully open-source, low-cost alternative purpose-built for unattended deployment in areas without grid power or cellular coverage. The system was validated through a multi-day field trial and dedicated communication tests, demonstrating a stable power conversion efficiency of 84–90%, a five-day autonomous operation without any deep-discharge event, high linearity (R2 = 0.9998) of the level module over a 0–2 m range with a resolution of approximately 1.94 mm per ADC count, and a reliable LoRa link of up to 8.51 km in an urban/suburban environment despite non-line-of-sight conditions. With an estimated hardware cost of approximately $100 USD per unit, the device represents a low-cost, low-maintenance tool capable of generating knowledge about water resources to optimize irrigation and crop management in the face of climate change.

Field instruments are an emerging topic because they facilitate the extraction of qualitative and quantitative information from samples at a sampling site. This work focused on the development of an open-source potentiostat, analyzing the construction feasibility and quality of a lab-made device with an all-in-one design, low cost, good response, and portability, compared to expensive, commercial, laboratory-oriented devices. The design and development of the hardware, as well as the corresponding software, was considered, allowing the device to be expandable in the future through upgrades. Thus, an economical and portable functional prototype was developed, with good linear response and the capacity to perform, in this first approach, cyclic, square wave, and stripping voltammetry with a range and sweep speed between ±2.048 V and 1000 mV/s, respectively, with waveform frequencies up to 110 Hz and an accuracy of ±1 nA.

Sustainable cities aim to have a lower environmental impact by reducing their carbon footprints as much as possible. The smart city paradigm based on the Internet of Things (IoT) is the natural approach to achieving this goal. Nevertheless, the proliferation of sensors and IoT technologies, along with the need for annotating real-time data, has promoted the need for light weight ontology-based models for IoT environments, such as IoT-Stream. The IoT-Stream model takes advantage of common knowledge sharing of the semantics while keeping queries and inferences simple. However, sensors in the IoT-Stream model are conceptualized as single entities, exluding further analysis concerning their features (energy consumption, cost, etc.) or application areas. In this article, we present a taxonomy of sensors that expands the original IoT-Stream model by facilitating the mapping of sensors/actuators and services in the context of smart cities in such a way that different applications can share information in a transparent way, avoiding unnecessary duplication of sensors and network infrastructure.

In this paper the design and implementation of an embedded system based on Flow-Batch methodology with a Quartz Crystal Microbalance (QCM) sensor technology and a commercial FPGA admittance meter is presented to detect the presence of arsenic in water. The system's performance was evaluated with lab made samples and it is foresee that this open source automated flow instrument could help develop analytical methodologies for the future quantification of this analyte. A description of the components is presented and assembling and operation instructions are provided together with the dynamic range and linear regression coefficients for the line and R.

Regardless of the extensive research conducted on large-scale evacuations, the instrumentation of these processes still represents an open issue for first response organizations. Self-evacuation of civilians that follows evacuation plans has shown to be feasible as early response to several natural disasters; however, the typical lack of interaction capability of the evacuees with first response organizations and emergency managers jeopardizes the effectiveness of these processes. This article proposes an IoT-based infrastructure that supports self-evacuation of civilians in mass processes, allowing people to participate as information providers and consumers. This infrastructure is the backbone of an ambient intelligence system used as a bridge between evacuees, first response units, and the emergency operation center managing the process. Depending on the people location and the status of the area, the system implements breadcrumbs that guide people to shelters and safe places. The proposed infrastructure includes (1) an architecture that captures the core design aspects of the solution and makes it reusable for other researchers, (2) an implementation of the system based on Raspberry Pi 3 devices with LoRa radio connectivity, (3) a mobile application that allows evacuees to interact with the evacuation system, and (4) a simplified algorithm to support the deployment of the IoT-based infrastructure into an urban area. The solution was evaluated using real measurements and simulations, and the obtained results are highly encouraging.

In this paper a methodology for teaching and learning the modeling of embedded systems and, in a more generic vision cyber-physical systems (CPS) is presented. To this end, a subset of tools from UML is used in an intuitive and ordered way starting with an informal description of the system until implementation details are obtained. However, the codification of the system is left out as the programming language depends on the hardware platform to be used. The method has been used in grade courses for several years now with an important accumulated experience that shows how students are able to adopt it and learn to elicit the different types of requirements, actors and functions.

The interaction among components of an IoT-based system usually requires using low latency or real time for message delivery, depending on the application needs and the quality of the communication links among the components. Moreover, in some cases, this interaction should consider the use of communication links with poor or uncertain Quality of Service (QoS). Research efforts in communication support for IoT scenarios have overlooked the challenge of providing real-time interaction support in unstable links, making these systems use dedicated networks that are expensive and usually limited in terms of physical coverage and robustness. This paper presents an alternative to address such a communication challenge, through the use of a model that allows soft real-time interaction among components of an IoT-based system. The behavior of the proposed model was validated using state machine theory, opening an opportunity to explore a whole new branch of smart distributed solutions and to extend the state-of-the-art and the-state-of-the-practice in this particular IoT study scenario.

The response to natural disasters usually requires evacuation procedures that should be followed in a quick and orderly fashion. While census data provide information on the population distribution during sleeping hours, the evacuation procedure may arrive at any moment of the day, even when people are not at home; e.g., in their daily activities. This particular situation causes preparedness plans based on census information to become minimally effective; therefore, more dynamic and context-aware strategies are required to properly address these evacuation processes. In this paper, an evacuation supporting system, based on IoT-networked devices, is proposed to guide people to safe places or shelters once the alert of an extreme event has been issued. The system is interactive and support crowd-sensing; this allows people to upload information on the state of the routes and the shelters, thus keep an updated status of the evacuation routes. The contribution of the paper is twofold. On one side, an evolutionary algorithm is proposed to provide coverage in a breadcrumb deployment of information posts called witness units. On the other, an application based on geographical information system is presented as an intermediary between the witness units and the users; this application guides people towards safe places or shelters.

This paper describes for the first time the use of emitter and receiver piezoelectric films coupled one in front of the other into a flow-batch analyzer for acoustic determination of free glycerol in biodiesel without chemicals/external pretreatment. Online extraction of free glycerol from biodiesel was carried out into aqueous solution without chemicals/external pretreatment. While the emitter piezoelectric is activated to sonicate the solution, the receiver piezoelectric translates the acoustic signal received into an electrical signal, which is measured and recorded by a digital oscilloscope. Multivariate calibration models were built for prediction of free glycerol concentration. In this sense, results of partial least square regression (PLS), the interval PLS (iPLS) and PLS coupled with the Successive Projections Algorithm for interval selection (iSPA-PLS) were compared. The proposed low-cost flow-batch analyzer exhibited good performance, satisfactory detection limit (0.12 mg kg(-1)) and a linear response from 72 to 372 mg kg(-1) of free glycerol in biodiesel. The procedure was successfully applied to the analysis of biodiesel samples, and the results agreed with the reference method (ASTM D6584-07) at 95% confidence level. (C) 2018 Elsevier B.V. All rights reserved.

Internet of Things (IoT) have become a hot topic since the official introduction of IPv6. Research on Wireless Sensors Networks (WSN) move towards IoT as the communication platform and support provided by the TCP/UDP/IP stack provides a wide variety of services. The communication protocols need to be designed in such a way that even simple microcontrollers with small amount of memory and processing speed can be interconnected in a network. For this different protocols have been proposed. The most extended ones, MQTT and CoAP, represent two different paradigms. In this paper, we present a CoAP extension to support soft real-time communications among sensors, actuators and users. The extension facilitates the instrumentation of applications oriented to improve the quality of life of vulnerable communities contributing to the social good.

A lab-made prototype consisting of a potentiostat with a flow-batch system was designed and implemented under the commercial off the shelf paradigm. The prototype is light-weight and suitable for laboratory performance. Its performance was evaluated with linear sweep voltammetry (LSV) study of ferrocyanide/ferricyanide redox couple and the obtained results were comparable to that obtained with a commercial potentiostat. The system was applied in the determination of lead in propolis samples. For this purpose, bismuth film electrode by square wave anodic stripping voltammetry (SWASV) was employed. The obtained results were validated by atomic emission spectroscopy with inductively coupled plasma and very good agreement was obtained.

This paper presents the experience of incorporating open hardware and open software paradigms to the microcontroller architecture and embedded systems course in the careers of Electronic Engineering and Computer Engineering. The traditional syllabus proposed in textbooks is changed and the use of Arduino platforms is incorporated in the first labs. The basis for this change comes from the “hands on learning” pedagogical paradigm that is partially implemented in the course.

This paper presents the experience of incorporating open hardware and open software paradigms to the microcontroller architecture and embedded systems course in the careers of Electronic Engineering and Computer Engineering. The traditional syllabus proposed in textbooks is changed and the use of Arduino platforms is incorporated in the first labs. The basis for this change comes from the "hands on learning" pedagogical paradigm that is partially implemented in the course.

Underwater sensor networks are becoming an important field of research, because of their everyday increasing application scope. Examples of their application areas are environmental and pollution monitoring (mainly oil spills), oceanographic data collection, support for submarine geolocalization, ocean sampling and early tsunamis alert. The challenge of performing underwater communications is well known, provided that radio signals are useless in this medium, and a wired solution is too expensive. Therefore, the sensors in these networks transmit their information using acoustic signals that propagate well under water. This data transmission type not only brings an opportunity, but also several challenges to the implementation of these networks, e.g., in terms of energy consumption, data transmission and signal interference. In order to help advance the knowledge in the design and implementation of these networks for monitoring underwater spaces, this paper proposes a MAC protocol for acoustic communications between the nodes, based on a self-organized time division multiple access mechanism. The proposal was evaluated using simulations of a real monitoring scenario, and the obtained results are highly encouraging.

This paper reports the experience of implementing a data logger for a diesel-electric locomotive using open hardware and software. The proposed system was designed for one of the main railway companies in Argentina under the requirement from the Government office for transport control security.

Underwater sensor networks are becoming an important field of research, because of its everyday increasing application scope. Examples of their application areas are environmental and pollution monitoring (mainly oil spills), oceanographic data collection, support for submarine geo-localization, ocean sampling and early tsunamis alert. It is well-known the challenge that represents to perform underwater communications provided that radio signals are useless in this medium and a wired solution is too expensive. Therefore, the sensors in these network transmit their information using acoustic signals that propagate well under water. This data transmission type bring an opportunity, but also several challenges to the implementation of these networks, e.g., in terms of energy consumption, data transmission and signal interference. Few proposals are available to deal with the problem in this particular application scenario, and these proposals does not address properly the transmission of underwater acoustic signals. In order to help advance the knowledge in the design and implementation of these networks, this paper proposes a MAC protocol for acoustic communications between the nodes based on a self-organized time division multiple access mechanism. The proposal is still preliminary and it has only been evaluated in the laboratory; however, it represents a highly promising behavior that make us expect interesting results in real-world scenarios.