Development of a fuzzy logic-based solar charge controller for charging lead-acid batteries

Este documento se considera que es una ponencia de congresos en lugar de un artículo.International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2019), Oct. 28-31 2019, Ambato (Ecuador)The design and implementation of a solar charge controller for lead-acid batteries is intended to supplement a component of the water purification module of the water treatment unit for natural disaster relief. This unit contains a solar panel system that supplies power to the module by charging batteries through a controller comprising an Atmega 328 processor. The solar panel feeds voltage to the batteries through fuzzy logic-based software, which allows up to 6 A DC to pass through the controller's power circuit. Consequently, the battery was charged in less time (an average of 7 h to reach maximum capacity), wherein battery lifespan is related to the charge wave frequency. Thus, our software may be adapted in different control algorithms without having to change hardware

CMOS Vision Sensors: Embedding Computer Vision at Imaging Front-Ends

CMOS Image Sensors (CIS) are key for imaging technol-ogies. These chips are conceived for capturing opticalscenes focused on their surface, and for delivering elec-trical images, commonly in digital format. CISs may incor-porate intelligence; however, their smartness basicallyconcerns calibration, error correction and other similartasks. The term CVISs (CMOS VIsion Sensors) definesother class of sensor front-ends which are aimed at per-forming vision tasks right at the focal plane. They havebeen running under names such as computational imagesensors, vision sensors and silicon retinas, among others. CVIS and CISs are similar regarding physical imple-mentation. However, while inputs of both CIS and CVISare images captured by photo-sensors placed at thefocal-plane, CVISs primary outputs may not be imagesbut either image features or even decisions based on thespatial-temporal analysis of the scenes. We may hencestate that CVISs are more “intelligent” than CISs as theyfocus on information instead of on raw data. Actually,CVIS architectures capable of extracting and interpretingthe information contained in images, and prompting reac-tion commands thereof, have been explored for years inacademia, and industrial applications are recently ramp-ing up.One of the challenges of CVISs architects is incorporat-ing computer vision concepts into the design flow. Theendeavor is ambitious because imaging and computervision communities are rather disjoint groups talking dif-ferent languages. The Cellular Nonlinear Network Univer-sal Machine (CNNUM) paradigm, proposed by Profs.Chua and Roska, defined an adequate framework forsuch conciliation as it is particularly well suited for hard-ware-software co-design [1]-[4]. This paper overviewsCVISs chips that were conceived and prototyped at IMSEVision Lab over the past twenty years. Some of them fitthe CNNUM paradigm while others are tangential to it. Allthem employ per-pixel mixed-signal processing circuitryto achieve sensor-processing concurrency in the quest offast operation with reduced energy budget.Junta de Andalucía TIC 2012-2338Ministerio de Economía y Competitividad TEC 2015-66878-C3-1-R y TEC 2015-66878-C3-3-

Extraordinary Passive Safety in Cars Using a Sensor Network Model

Context: The automobile industry has included active and passive safety. Active safety incorporates elements to avoid crashes and collisions. Some elements are ABS brakes and stabilization bars, among others. On the other hand, passive safety avoids or minimizes damage to the occupants in the event of an accident. Some passive safety features include seat belts and front and curtain airbags for the driver and other occupants. Method: In this research work, we propose a new category called Extraordinary Passive Safety (XPS). A model of a sensor network was designed to inspect the conditions inside the car to detect fire, smoke, gases, and extreme temperatures. The sensors send data to a device (DXPS) capable of receiving and storing the data. Results: Each sensor collects data and sends it to the DXPS every period. The sensor sends 0s while there is no risk, and 1s when it detects a risk. When the DXPS receives a 1, the pattern is evaluated, and the risk is identified. Since there are several sensors, the reading pattern is a set of 0s (000000). When a pattern with one or more 1s (000100, 010101) is received, the DXPS can send an alert or activate a device. Conclusions: The proposed solution could save the lives of children left in the car or people trapped when the car catches fire. As future work, it is intended to define the devices to avoid or minimize damage to the occupants such as oxygen supply, gas extraction, regulating the temperature, among other

Controls and Automation Research in Space Life Support

A highly controlled and automated life support system has long been a NASA goal. It is usually assumed that life support for future long duration missions will use physical/chemical recycling systems that substantially close the oxygen and water circulation loops. Such a tightly coupled life support system has been thought to require an overall supervisory control system to minimize crew operation and maintenance activities. The International Space Station (ISS) Environmental Control and Life Support System (ECLSS) was at first expected to have supervisory control and automation. After this was found infeasible during the design of the ISS ECLSS in the early 1990's, it was then expected that the ISS or future mission systems would be upgraded to meet the original expectations. Since then NASA has extensively researched life support system controls and automation. Automation and Artificial Intelligence (AI) have gone through several cycles of enthusiasm and neglect before their recent great achievements, and NASA life support interest has similarly varied. Since the ISS ECLSS was launched, its on-board operational problems have led NASA to deemphasize system level controls and automation in favor of improving subsystem reliability and maintainability. Recent work has investigated supervisory control for a system similar to the ISS ECLSS. This paper reviews past planning and work on the supervisory control of closed, integrated physical/chemical life support systems similar to the ISS ECLSS and its precursors dating back to the 1960's

Mission Aware Energy Saving Strategies For Army Ground Vehicles

Fuel energy is a basic necessity for this planet and the modern technology to perform many activities on earth. On the other hand, quadrupled automotive vehicle usage by the commercial industry and military has increased fuel consumption. Military readiness of Army ground vehicles is very important for a country to protect its people and resources. Fuel energy is a major requirement for Army ground vehicles. According to a report, a department of defense has spent nearly $13.6 billion on fuel and electricity to conduct ground missions. On the contrary, energy availability on this plant is slowly decreasing. Therefore, saving energy in Army ground vehicles is very important. Army ground vehicles are embedded with numerous electronic systems to conduct missions such as silent and normal stationary surveillance missions. Increasing electrical energy consumption of these systems is influencing higher fuel consumption of the vehicle. To save energy, the vehicles can use any of the existing techniques, but they require complex, expensive, and time consuming implementations. Therefore, cheaper and simpler approaches are required. In addition, the solutions have to save energy according to mission needs and also overcome size and weight constraints of the vehicle. Existing research in the current literature do not have any mission aware approaches to save energy. This dissertation research proposes mission aware online energy saving strategies for stationary Army ground vehicles to save energy as well as to meet the electrical needs of the vehicle during surveillance missions. The research also proposes theoretical models of surveillance missions, fuzzy logic models of engine and alternator efficiency data, and fuzzy logic algorithms. Based on these models, two energy saving strategies are proposed for silent and normal surveillance type of missions. During silent mission, the engine is on and batteries power the systems. During normal surveillance mission, the engine is on, gear is on neutral position, the vehicle is stationary, and the alternator powers the systems. The proposed energy saving strategy for silent surveillance mission minimizes unnecessary battery discharges by controlling the power states of systems according to the mission needs and available battery capacity. Initial experiments show that the proposed approach saves 3% energy when compared with the baseline strategy for one scenario and 1.8% for the second scenario. The proposed energy saving strategy for normal surveillance mission operates the engine at fuel-efficient speeds to meet vehicle demand and to save fuel. The experiment and simulation uses a computerized vehicle model and a test bench to validate the approach. In comparison to vehicles with fixed high-idle engine speed increments, experiments show that the proposed strategy saves fuel energy in the range of 0-4.9% for the tested power demand range of 44-69 kW. It is hoped to implement the proposed strategies on a real Army ground vehicle to start realizing the energy savings

Cyber-Physical Embedded Systems with Transient Supervisory Command and Control: A Framework for Validating Safety Response in Automated Collision Avoidance Systems

The ability to design and engineer complex and dynamical Cyber-Physical Systems (CPS) requires a systematic view that requires a definition of level of automation intent for the system. Since CPS covers a diverse range of systemized implementations of smart and intelligent technologies networked within a system of systems (SoS), the terms “smart” and “intelligent” is frequently used in describing systems that perform complex operations with a reduced need of a human-agent. The difference between this research and most papers in publication on CPS is that most other research focuses on the performance of the CPS rather than on the correctness of its design. However, by using both human and machine agency at different levels of automation, or autonomy, the levels of automation have profound implications and affects to the reliability and safety of the CPS. The human-agent and the machine-agent are in a tidal lock of decision-making using both feedforward and feedback information flows in similar processes, where a transient shift within the level of automation when the CPS is operating can have undesired consequences. As CPS systems become more common, and higher levels of autonomy are embedded within them, the relationship between human-agent and machine-agent also becomes more complex, and the testing methodologies for verification and validation of performance and correctness also become more complex and less clear. A framework then is developed to help the practitioner to understand the difficulties and pitfalls of CPS designs and provides guidance to test engineering design of soft computational systems using combinations of modeling, simulation, and prototyping

Enhanced clustering based routing protocol in vehicular ad‐hocnetworks

A vehicular ad‐hoc network (VANET) is derived from a mobile ad‐hoc network that is a part of less infrastructure network design. Vehicular communication in VANET can be achieved using vehicle‐to‐infrastructure (V2I) and vehicle‐to‐vehicle (V2V) communication. A vehicle communicates with other vehicles through onboard units while communicating with roadside units in an infrastructure mode. Secure clustering is required for the communication between nodes in the whole network. The fundamental problem with the VANET is the instability of the network that occurs due to vehicles' mobile nature, which decreases the network's efficiency. This research proposes an enhanced cluster‐based lifetime protocol ECBLTR that focuses on maximising the network's stability of routing and average throughput. The Sugeno model fuzzy inference system is used for assessing the cluster head (CH) that takes residual energy, local distance, node degree, concentration, and distance from the base station as input parameters. Our enhanced routing protocol shows that the proper channel model with an efficient routing protocol enhances the link throughput of the VANET for fixed network size. Our results show an efficient selection method of CH through the fuzzy system and a 10% increase in network lifetime. Furthermore, performance evaluation also demonstrates the impact of network sizes and routing protocols on packet delivery ratio and packet loss, average end‐to‐end delay, and overhead transmission

A Comparative and Analytical Review of Iot-Enabled Smart Accidental Management Systems

One of the most important issues that emerging nations are addressing is road accidents. It is important to develop smart accidental management systems with low cost and efforts to prevent accidents and causalities. The amalgamation of Intelligent Transportation Systems (ITS) and Information and Communications Technology (ICT) is expected to dramatically change how people experience driving by enabling cutting-edge traffic monitoring and incident detection strategies. This analysis focuses on various components of SAMS, such as sensor networks, communication protocols, data processing techniques, and decision-making algorithms. It examines how these components work together to create a connected infrastructure capable of detecting and responding to accidents promptly. The review highlights the role of data analytics in enhancing accident prediction and prevention. By processing and analyzing enormous real-time data from cameras, sensors, and other sources, IoT-driven SAMS can identify patterns and anomalies, allowing for proactive measures to avoid accidents in various settings, including transportation, industries, and public spaces

An intelligent automobile diagnostic system

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (p. 72-74).by Marcus Kramer.M.Eng