This paper presents the design and implementation of an autonomous indoor houseplant irrigation robot operating under the ROS2 framework. The robot prototype integrates locomotion, water delivery, power management, se...
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ISBN:
(纸本)9798350366457;9798350366440
This paper presents the design and implementation of an autonomous indoor houseplant irrigation robot operating under the ROS2 framework. The robot prototype integrates locomotion, water delivery, power management, sensors, and high-level control systems. A YOLOv8-based vision system, trained on a custom houseplant dataset, detects and localizes plants for precise irrigation. Robot localization and mapping use ROS2 SLAM Toolbox with 2D LIDAR, for autonomous navigation and irrigation via ROS2's Nav2 path planning. Wireless communication is achieved through an ad-hoc mesh network connecting the main computer with distributed microcontrollers. The prototype demonstrates key autonomous functions, as well as acknowledging limitations, presenting opportunities for future enhancements to improve robustness and practical applicability in home automation.
The proceedings contain 95 papers. The topics discussed include: towards LLM-powered ambient sensor based multi-person human activity recognition;SwitchFlow: optimizing HPC workflow performance with heterogeneous serv...
ISBN:
(纸本)9798331515966
The proceedings contain 95 papers. The topics discussed include: towards LLM-powered ambient sensor based multi-person human activity recognition;SwitchFlow: optimizing HPC workflow performance with heterogeneous serverless frameworks;mmHRR: monitoring heart rate recovery with millimeter wave radar;accurate traffic state prediction with deep learning – analyzing statistical aides for identifying anomalous traffic trends;BreathPass: ultrasonic authentication by chest and abdomen movement while breathing;Soundflower: a robust sound source localization system for voice assistants;prolonging the range of low-power visible light communication systems with M-FSK;and A QoE-aware adaptive energy-efficient transmission scheduling method.
This research investigates the limitations of current quantum hardware in fulfilling the computational demands of quantum neural networks. It introduces an optimized circuit computed method leveraging bit splitting wi...
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The proceedings contain 9 papers. The special focus in this conference is on distributedcomputing and Artificial Intelligence. The topics include: A Deep Learning-Based OCR System Implementation for Traceability...
ISBN:
(纸本)9783031820724
The proceedings contain 9 papers. The special focus in this conference is on distributedcomputing and Artificial Intelligence. The topics include: A Deep Learning-Based OCR System Implementation for Traceability Ensurement in a Metal Manufacturing Workshop;dimensional Reduction Techniques for the Characterization of Behavioral Patterns in Dairy Cows;geothermal Heat Exchanger’s Temperature Input sensor Prediction Based on Deep Learning Modelling Technique;a Hybrid Intelligence Model Forecasts the Temperature of a Battery Used in Electric Vehicles;a Comparative Analysis of Algorithms and Metrics to Perform Clustering;wind Speed Virtual sensor for Small Wind Turbine;reconstructing Turbulence-Distorted Wavefronts Through Laser-Beam Profiles.
A network is a distributed dynamic multi-hop MANET (mobile ad-hoc network). It's critical to create a successful ad-hoc network routing system in order to address the issue with MANET-based WSN (Wireless sensor Ne...
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Source localization is an important problem in wireless sensor networks. However, current localization methods mainly consider homogeneous sensor with data such as distance or angle and lack the analysis for localizat...
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Self-consumption is developing worldwide to increase renewable electricity consumption and reduce electricity bills. It can be carried out individually or collectively (grouping several entities), but is generally res...
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ISBN:
(纸本)9798331507879;9798331507862
Self-consumption is developing worldwide to increase renewable electricity consumption and reduce electricity bills. It can be carried out individually or collectively (grouping several entities), but is generally restricted geographically. In datacenters, one may use load shifting to benefit from the self-consumption tariffs, at the cost of increasing energy consumption. An alternative would be to extend the self-consumption rules to wider perimeters. This paper proposes a comparative study on several aspects influencing the collective self-consumption (CSC) of an Edge infrastructure, including spatial load shifting, temporal load shifting and extending the current rules to encompass wider geographical boundaries. Spatial shifting under the current CSC scheme is found more cost-effective (3.9% of cost reduction) with a negligible increase in energy consumption (0.19%), compared to the revised definition of collective self-consumption which leads to 3.7% cost reduction and no increase in energy consumption. Moreover, allowing up to 10% of the user tasks to be shifted in time can further increase the self-consumption rate by 1.3%.
Visual computing is vital for numerous applications. In conventional visual computingsystems, CMOS image sensors (CIS) act as pure imaging devices for capturing images, however, recent CIS designs increasingly integr...
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Middle ear effusion is a common symptom of otitis media, the reactive physical manifestation of otitis media (OM) in children's middle ear. However, diagnosing MEE for little children at home is troublesome due to...
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ISBN:
(纸本)9798350339864
Middle ear effusion is a common symptom of otitis media, the reactive physical manifestation of otitis media (OM) in children's middle ear. However, diagnosing MEE for little children at home is troublesome due to their difficulty cooperating and the caregiver's lack of medical knowledge. To this end, we propose EarSonar, a novel acoustic-based MEE diagnostic system. The principle behind EarSonar is that the acoustic absorption effect exists in ear scenarios, and the volume of middle ear fluid can markedly affect the absorbed spectrum energy. By automatically eliminating the impact of potential interference factors and identifying the representative frequency range with the typical reaction of acoustic absorption, EarSonar captures fine-grained signal features on absorbed spectrum energy and models the intrinsic relationship between acoustic absorption and the volume of the filler fluid in the eardrum. On that basis, EarSonar extracts the features of the MEE signal segment and uses k-means clustering to classify middle ear effusion status. We conducted a test on 112 adolescents aged 4-6. We divided the degree of middle ear effusion into three grades. The final average detection accuracy rate exceeds 92%, which is 8% higher than the previous method. We have implemented a proof-of-concept prototype of EarSonar by building upon earphones embedded with a microphone and speaker. Experimental results demonstrate a feasible and effective way to turn earphones into potential home-use MEE screening tools.
This paper focuses on the challenges of modeling and verifying symmetric distributed algorithms with point-to-point and bidirectional communications using the SPIN model checker. In this paper, we first state the prob...
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