A network architecture for high volume data collection in agricultural applications

An important requirement for Internet of Things applications is the ability to provide fast and energy efficient data collection from wireless sensors. When sensor nodes are located far from the data collection point, currently available long range protocols present challenges associated with a very low data rate and often unreliable connections resulting in excessive energy consumption related to data transmission. To address this problem, we propose a simple and energy-efficient data collection architecture for smart agricultural purposes which require wireless sensing. The architecture involves data collection from nodes located in remote fields or on animals leveraging off the use of drones as a data collection mechanism. In particular, drones can fly over the desired areas (points) and collect high volumes of data that would be otherwise difficult to transfer directly to the sink in a reasonable amount of time and using reasonable amounts of energy. We describe the different components and stages that constitute the proposed architecture emphasizing the networking component. We propose the use of different communication technologies, such as LoRa and WiFi, depending on the data collection requirements. We present an in-lab development of this architecture as a proof-of-concept as well as preliminary results for the architecture. The results reveal that the proposed solution is potentially capable of achieving data collection at high volume, however, the performance does not consider the highest spreading factors of LoRa

D3S: A Framework for Enabling Unmanned Aerial Vehicles as a Service

In this paper, we consider the use of UAVs to provide wireless connectivity services, for example after failures of wireless network components or to simply provide additional bandwidth on demand, and introduce the concept of UAVs as a service (UaaS). To facilitate UaaS, we introduce a novel framework, dubbed D3S, which consists of four phases: demand, decision, deployment, and service. The main objective of this framework is to develop efficient and realistic solutions to implement these four phases. The technical problems include determining the type and number of UAVs to be deployed, and also their final locations (e.g., hovering or on-ground), which is important for serving certain applications. These questions will be part of the decision phase. They also include trajectory planning of UAVs when they have to travel between charging stations and deployment locations and may have to do this several times. These questions will be part of the deployment phase. The service phase includes the implementation of the backbone communication and data routing between UAVs and between UAVs and ground control stations

Unlocking Solar Power For Surveillance A Review Of Solar Powered CCTV And Surveillance Technologies

Solar-powered surveillance technologies have gained prominence for their sustainable, autonomous, and versatile solutions. This comprehensive review explores three key solar-powered surveillance technologies: solar-powered CCTV cameras, solar drones, and solar-powered sensor networks. Each technology offers distinct strengths and weaknesses, making them suitable for various applications. Solar-powered CCTV cameras provide adaptability, energy independence, and rapid deployment, while solar drones offer an aerial perspective, extended endurance, and versatility. Solar-powered sensor networks excel in localized environmental monitoring. The choice of technology depends on factors such as the surveillance environment, budget constraints, required surveillance range, and specific monitoring needs. Organizations can benefit from hybrid solutions that integrate multiple technologies for comprehensive coverage. Future trends include advanced energy storage solutions, AI integration, enhanced power efficiency, and cloud-based data analytics, promising to improve performance and sustainability. Public-private collaborations and sustainable urban planning initiatives will drive further adoption and integration. Solar-powered surveillance technologies empower effective and environmentally sustainable surveillance solutions, contributing to a safer and more sustainable future

Wireless Sensor Network Based Monitoring System: Implementation, Constraints, and Solution

Wireless Sensor Network (WSN) is a collection of sensors communicating at close range by forming a wireless-based network (wireless). Since 2015 research related to the use of WSN in various health, agriculture, security industry, and other fields has continued to grow. One interesting research case is the use of WSN for the monitoring process by collecting data using sensors placed and distributed in locations based on a wireless system. Sensors with low power, multifunction, supported by a combination of wireless network, microcontroller, memory, operating system, radio communication, and energy source in the form of an integrated battery enable a monitoring process of the monitoring area to run properly. The implementation of the wireless sensor network includes five main parts, namely sender, receiver, wireless transmission media, data/information, network architecture/configuration, and network management. Network management itself includes network configuration management, network performance management, network failure management, network security management, and network financing management. The main obstacles in implementing a wireless sensor network include three things: an effective and efficient data sending/receiving process, limited and easily depleted sensor energy/power, network security, and data security that is vulnerable to eavesdropping and destruction. This paper presents a taxonomy related to the constraints in implementing Wireless Sensor Networks. This paper also presents solutions from existing studies related to the constraints of implementing the WSN. Furthermore, from the results of the taxonomy mapping of these constraints, new gaps were identified related to developing existing research to produce better solutions

Scenarios for Educational and Game Activities using Internet of Things Data

Raising awareness among young people and changing their behavior and habits concerning energy usage and the environment is key to achieving a sustainable planet. The goal to address the global climate problem requires informing the population on their roles in mitigation actions and adaptation of sustainable behaviors. Addressing climate change and achieve ambitious energy and climate targets requires a change in citizen behavior and consumption practices. IoT sensing and related scenario and practices, which address school children via discovery, gamification, and educational activities, are examined in this paper. Use of seawater sensors in STEM education, that has not previously been addressed, is included in these educational scenaria