Real-time image streaming over a low-bandwidth wireless camera network

In this paper we describe the recent development of a low-bandwidth wireless camera sensor network. We propose a simple, yet effective, network architecture which allows multiple cameras to be connected to the network and synchronize their communication schedules. Image compression of greater than 90% is performed at each node running on a local DSP coprocessor, resulting in nodes using 1/8th the energy compared to streaming uncompressed images. We briefly introduce the Fleck wireless node and the DSP/camera sensor, and then outline the network architecture and compression algorithm. The system is able to stream color QVGA images over the network to a base station at up to 2 frames per second. © 2007 IEEE

Springbrook: Challenges in developing a long-term, rainforest wireless sensor network

We describe the design, development and learnings from the first phase of a rainforest ecological sensor network at Springbrook - part of a World Heritage precinct in South East Queensland. This first phase is part of a major initiative to develop the capability to provide reliable, long-term monitoring of rainforest ecosystems. We focus in particular on our analysis around energy and communication challenges which need to be solved to allow for reliable, long-term deployments in these types of environments

A Wireless Sensor Network Based Solar Powered Harvesting System for Aquaculture

Despite improvements in battery technology and declines in electronics power demands, many new applications in wireless sensor networks (WSNs) are taking into account increasing power requirements. Furthermore, since in WSNs it is frequently desirable to deploy nodes in unobtainable places, it might be impossible to provide large enough power for such applications given the fact that battery replacement is not practicable. This results in significant interests in designing sensor nodes with the capability of extracting electrical energy from surrounding ambient sources. The ultimate goal of this research is to achieve a perpetually powered system without a necessary periodical maintenance for battery replacement or recharging. The energy harvesting system developed for this research has been experimentally verified and can increase the lifetime of an entire network to reach that of its individual hardware components. We realized a maximum power point tracking (MPPT) algorithm that could switch power source according to light conditions to ensure the continuous stable operation

A framework for energy based performability models for wireless sensor networks

A novel idea of alternating node operations between Active and Sleep modes in Wireless Sensor Network (WSN) has successfully been used to save node power consumption. The idea which started off as a simple implementation of a timer in most protocols has been improved over the years to dynamically change with traffic conditions and the nature of application area. Recently, use of a second low power radio transceiver to triggered Active/Sleep modes has also been made. Active/Sleep operation modes have also been used to separately model and evaluate performance and availability of WSNs. The advancement in technology and continuous improvements of the existing protocols and application implementation demands continue to pose great challenges to the existing performance and availability models. In this study the need for integrating performance and availability studies of WSNs in the presence of both channel and node failures and repairs is investigated. A framework that outlines and characterizes key models required for integration of performance and availability of WSN is in turn outlined. Possible solution techniques for such models are also highlighted. Finally it is shown that the resulting models may be used to comparatively evaluate energy consumption of the existing motes and WSNs as well as deriving required performance measures

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

A Survey on Investigating the Need for Intelligent Power-Aware Load Balanced Routing Protocols for Handling Critical Links in MANETs

In mobile ad hoc networks connectivity is always an issue of concern. Due to dynamism in the behavior of mobile nodes, efficiency shall be achieved only with the assumption of good network infrastructure. Presence of critical links results in deterioration which should be detected in advance to retain the prevailing communication setup. This paper discusses a short survey on the specialized algorithms and protocols related to energy efficient load balancing for critical link detection in the recent literature. This paper also suggests a machine learning based hybrid power-aware approach for handling critical nodes via load balancing