With climate change and global warming in mind, vertical farms, hydroponics and urban greenhouses can now be found in many cities worldwide as we transform the ways we produce food. Additionally, recent implications of the COVID-19 pandemic prove that as a society we can harness the benefit of remote monitoring and automation for controlled-environment agriculture and horticulture.The subject matter of this paper is implementation of a solarpowered, Internet of Things (IoT) based Real-time Autonomous Horticulture Monitoring System (RAHMS). The RAHMS integrates a mobile application for viewing the greenhouse crop data and camera feed of plants, and interacts with cloud databases such as Firebase and MATLAB ThingSpeak for the scalability. In particular, a simple and distinctive design of a solar-powered, low energy consuming, and inexpensive greenhouse monitoring system is presented. The paper outlines RAHMS design methodology and showcases a proof-of-concept prototype with its core hardware and software components. The proposed system has a potential to further advance the practical aspects of the remote solutions for the cultivation and monitoring of horticulture and controlled-environment agriculture.
This paper presents the result of a pilot project of London Metropolitan University, aiming at developing a set of urban data services in support of the local communities in several boroughs of the city of London. They are targeting the health and well-being of the citizens by analyzing different types of information from a number of data sources -environmental sensors, geolocation information, and models of the urban infrastructure. Unlike the complex government projects covering large urban areas, which require significant resources and typically involve large service providers operating public clouds, our project targets local communities with limited capabilities by utilizing the concept of a private cloud running on commodity infrastructure within their reach. By employing a number of proven data technologies, software tools, and AI methods the project delivers a comprehensive picture of urban life. The first phase of the project reported here focuses on outdoor and indoor pollution, which are the keys for addressing many local community activities such as environment protection, urban planning, local transport, communal housing, and social services within the area.
Smart city is no longer fiction, which targets the futureit is now around us and requires immediate action in different directions: environment, transport, energy, social and cultural life, healthcare, etc. This article presents the current efforts of GATE Institute at Sofia University for building an urban data space based on data from a variety of sources in the Bulgarian capital. It has an open architecture, based on a private cloud, which allows the integration of diverse data and provides different data processing capabilities and services necessary to build integral data spaces. The pilot implementation currently performs monitoring and analysis of the environmental factors in Sofia using a set of bespoke components, which implement data management and data analysis algorithms from simple filtering and correlation to data analytics and prediction using historical data, static modelled data and dynamic data from environmental sensors in real-time. It serves as a basis for data enrichment based on different sources and cross-domain analysis using a variety of methods.This new opportunity has a huge potential and will have a significant impact on urban lifefrom planning the infrastructure and managing the communal services to the personalization of social services for the citizens.
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