IoT Platform to augment Solar Tree as Smart Highway Street Light with Ambient Monitoring Capability
06 Jul 2019-pp 1-6
TL;DR: The presented IoT network aims for enhancing the capabilities of the solar tree beyond just a power generation device to an application such as security, surveillance, pollution monitoring and many more.
Abstract: The presented work describes an interconnected multi-server IoT network for monitoring and control of smart solar tree. The IoT enabled solar tree is introduced as a smart street light with air quality monitoring capability and has been implemented in the Central Electronics Engineering Research Institute, Pilani. The presented network is a three-layer architecture with a sensor node at the lowermost layer for collecting the sensor data. The solar tree server above it performs the sampling of the data by triggering the software for sensor node. Upon successful data collection, the tree server communicates the same to the central server which is responsible for aggregation, visualization, storage, analysis and control of all the connected solar trees. The paper also discusses the implementation aspect of the network and presents the collected data from the solar tree. The presented IoT network aims for enhancing the capabilities of the solar tree beyond just a power generation device to an application such as security, surveillance, pollution monitoring and many more. At present, the work discussed is towards self-sustained street light with ambient monitoring capability.
Citations
More filters
TL;DR: In this article , the photovoltaic solar tree is used to increase the efficiency of PV systems by reducing the occupied area and optimizing the orientation angles of the panels, which can be used for other purposes such as crop production and parking.
Abstract: The generation of photovoltaic solar energy worldwide has increased significantly in recent years. This is mainly due to the growing demand of society for electricity, the need to reduce environmental impacts, and costs of such technology. The installation of a photovoltaic system with horizontally fixed panels requires a significant unshaded area, which has become increasingly scarce, especially in urban centers. The photovoltaic solar tree is a strategy used to increase the efficiency of photovoltaic systems by reducing the occupied area and optimizing the orientation angles of the panels. The originality of this work was that, through a literature review in different researches, seven relevant parameters related to solar photovoltaic trees were analyzed: (i) modeling and simulation, (ii) tree topology, (iii) orientation of the panels, (iv) constructive characteristics, (v) solar tracking, (vi) occupied area and (vii) site multiple uses. It was found that the photovoltaic solar tree is an interesting alternative to generate renewable energy for places without large enough areas, which can be used for other purposes, such as crop production and parking. Finally, it was concluded that, to date, there are no studies available in the literature on the optimization of photovoltaic generation per area for different topologies of known solar trees.
TL;DR: In this article , different renewable energy sources (PV, wind generators) have been discussed to be installed around the RTU campus and the profiles of electric power consumption are analyzed for one faculty and sport centre.
Abstract: Race to Zero challenge is a world-wide activity for the universities and colleges to foster the climate goals. This paper analyses the potential of Riga Technical University (RTU) for this action. Different renewable energy sources (PV, wind generators) have been discussed to be installed around the RTU campus. The profiles of electric power consumption are analysed for one faculty and sport centre. The consumption profiles show the amount of power demanded during the working hours, weekends and at night. Energy yield assessment on the roofs is made for two buildings where the configuration of PV panel placement and orientation are analysed that in turn is reflected in the energy generation profile. SCADA system is considered as a monitoring and control tool to visualize power generation and control of the power flow within the system elements.
References
More filters
01 Jan 2016
TL;DR: In this article, a cost effective methodology based on IoT to remotely monitor a solar photovoltaic plant for performance evaluation is discussed, which will facilitate preventive maintenance, fault detection, historical analysis of the plant in addition to real time monitoring.
Abstract: Using the Internet Of Things Technology for supervising solar photovoltaic power generation can greatly enhance the performance, monitoring and maintenance of the plant. With advancement of technologies the cost of renewable energy equipments is going down globally encouraging large scale solar photovoltaic installations. This massive scale of solar photovoltaic deployment requires sophisticated systems for automation of the plant monitoring remotely using web based interfaces as majority of them are installed in inaccessible locations and thus unable to be monitored from a dedicated location. The discussion in this paper is based on implementation of new cost effective methodology based on IoT to remotely monitor a solar photovoltaic plant for performance evaluation. This will facilitate preventive maintenance, fault detection, historical analysis of the plant in addition to real time monitoring.
143 citations
TL;DR: This paper surveys and compares accelerometer signals classification methods to enable IoT for rehabilitation and elderly monitoring for active aging and considers two functions useful for such treatments: activity recognition and movement recognition.
Abstract: Rehabilitation and elderly monitoring for active aging can benefit from Internet of Things (IoT) capabilities in particular for in-home treatments. In this paper, we consider two functions useful for such treatments: 1) activity recognition (AR) and 2) movement recognition (MR). The former is aimed at detecting if a patient is idle, still, walking, running, going up/down the stairs, or cycling; the latter individuates specific movements often required for physical rehabilitation, such as arm circles, arm presses, arm twist, curls, seaweed, and shoulder rolls. Smartphones are the reference platforms being equipped with an accelerometer sensor and elements of the IoT. The work surveys and compares accelerometer signals classification methods to enable IoT for the aforementioned functions. The considered methods are support vector machines (SVMs), decision trees, and dynamic time warping. A comparison of the methods has been proposed to highlight their performance: all the techniques have good recognition accuracies and, among them, the SVM-based approaches show an accuracy above 90% in the case of AR and above 99% in the case of MR.
130 citations
"IoT Platform to augment Solar Tree ..." refers background in this paper
...Triggered by the development in the IoT domain, smart solutions have been proposed to visualize smart city concepts [1]–[3]....
[...]
TL;DR: The SSL system is presented, a framework developed for a dynamic switching of street lamps based on pedestrians' locations and desired safety (or “fear”) zones, a first approach to accomplish the demand for flexible public lighting systems.
Abstract: Purpose – Conventional street lighting systems in areas with a low frequency of passersby are online most of the night without purpose. The consequence is that a large amount of power is wasted meaninglessly. With the broad availability of flexible‐lighting technology like light‐emitting diode lamps and everywhere available wireless internet connection, fast reacting, reliably operating, and power‐conserving street lighting systems become reality. The purpose of this work is to describe the Smart Street Lighting (SSL) system, a first approach to accomplish the demand for flexible public lighting systems.Design/methodology/approach – This work presents the SSL system, a framework developed for a dynamic switching of street lamps based on pedestrians' locations and desired safety (or “fear”) zones. In the developed system prototype, each pedestrian is localized via his/her smartphone, periodically sending location and configuration information to the SSL server. For street lamp control, each and every lampp...
100 citations
"IoT Platform to augment Solar Tree ..." refers background in this paper
...Street light control based on wireless communication has been presented in multiple works [4], [5]....
[...]
01 Aug 2017
TL;DR: A collaborative industry-university-government project to create a smart monitoring device (SMD) and establish associated algorithms and software for fault detection and solar array management and a Cyber-Physical project, whose aim is to improve solar array efficiency and robustness using new machine learning and imaging methods, was launched recently.
Abstract: Photovoltaic (PV) array analytics and control have become necessary for remote solar farms and for intelligent fault detection and power optimization. The management of a PV array requires auxiliary electronics that are attached to each solar panel. A collaborative industry-university-government project was established to create a smart monitoring device (SMD) and establish associated algorithms and software for fault detection and solar array management. First generation smart monitoring devices (SMDs) were built in Japan. At the same time, Arizona State University initiated research in algorithms and software to monitor and control individual solar panels. Second generation SMDs were developed later and included sensors for monitoring voltage, current, temperature, and irradiance at each individual panel. The latest SMDs include a radio and relays which allow modifying solar array connection topologies. With each panel equipped with such a sophisticated SMD, solar panels in a PV array behave essentially as nodes in an Internet of Things (IoT) type of topology. This solar energy IoT system is currently programmable and can: a) provide mobile analytics, b) enable solar farm control, c) detect and remedy faults, d) optimize power under different shading conditions, and e) reduce inverter transients. A series of federal and industry grants sponsored research on statistical signal analysis, communications, and optimization of this system. A Cyber-Physical project, whose aim is to improve solar array efficiency and robustness using new machine learning and imaging methods, was launched recently.
65 citations
"IoT Platform to augment Solar Tree ..." refers background in this paper
...In recent years, enhancement of solar panels with features such as remote monitoring and energy management have been demonstrated through IoT [17]–[19]....
[...]
TL;DR: An energy prediction algorithm that uses the light intensity of fluorescent lamps in an indoor environment to accurately estimate the amount of energy that will be harvested by a solar panel using a weighted average for light intensity is proposed.
Abstract: The solar powered energy harvesting sensor node is a key technology for Internet of Things (IoT), but currently it offers only a small amount of energy storage and is capable of harvesting only a trivial amount of energy. Therefore, new technology for managing the energy associated with this sensor node is required. In particular, it is important to manage the transmission interval because the level of energy consumption during data transmission is the highest in the sensor node. If the proper transmission interval is calculated, the sensor node can be used semi-permanently. In this study, the authors propose an energy prediction algorithm that uses the light intensity of fluorescent lamps in an indoor environment. The proposed algorithm can be used to accurately estimate the amount of energy that will be harvested by a solar panel using a weighted average for light intensity. Then, the optimal transmission interval is calculated using the amount of predicted harvested energy and residual energy. The results from the authors' experimental testbeds show that their algorithm's performance is better than the existing approaches. The energy prediction error of their algorithm is approximately 0.5%.
47 citations