Technical Reports
Parent: Center for Embedded Network Sensing
eScholarship stats: Breakdown by Item for November, 2024 through February, 2025
| Item | Title | Total requests | Download | View-only | %Dnld |
|---|---|---|---|---|---|
| 4zw2f3s6 | Colibration: A Collaborative Approach to In-Place Sensor Calibration | 108 | 20 | 88 | 18.5% |
| 8wb43238 | Ambulation: a tool for monitoring mobility patterns over time using mobile phones | 69 | 5 | 64 | 7.2% |
| 2tp2w3g0 | Time Synchronization in Wireless Sensor Networks | 68 | 46 | 22 | 67.6% |
| 7qd6q8qm | Smart Screen Management on Mobile Phones | 56 | 4 | 52 | 7.1% |
| 88b146bk | The Atom LEAP Platform For Energy-Efficient Embedded Computing | 54 | 3 | 51 | 5.6% |
| 2t29v9wj | Nonmyopic Adaptive Informative Path Planning for Multiple Robots | 53 | 8 | 45 | 15.1% |
| 81s2s0t2 | Accurate Energy Attribution and Accounting for Multi-core Systems | 45 | 7 | 38 | 15.6% |
| 8v26b5qh | Rapid Deployment with Confidence:Calibration and Fault Detection in Environmental Sensor Networks | 44 | 12 | 32 | 27.3% |
| 95t603tj | Participatory Sensing for Community Data Campaigns: A case study | 41 | 10 | 31 | 24.4% |
| 7bx0g78h | Participatory Design of Sensing Networks: Strengths and Challenges | 40 | 8 | 32 | 20.0% |
| 4jd4f32h | Real-Time Adaptive Management of Soil Salinity Using a Receding Horizon Control Algorithm: A Pilot-Scale Demonstration | 39 | 6 | 33 | 15.4% |
| 8q70p81g | A Receding Horizon Control Algorithm for Adaptive Management of Soil Moisture and Chemical Levels during Irrigation | 39 | 12 | 27 | 30.8% |
| 5ft2s305 | The Low Power Energy Aware Processing (LEAP) Embedded Networked Sensor System | 37 | 13 | 24 | 35.1% |
| 47k5b67p | The Energy Endoscope: Real-time Detailed Energy Accounting for Wireless Sensor Nodes | 35 | 8 | 27 | 22.9% |
| 7617924b | Achieving Participatory Privacy Regulation: Guidelines for CENS Urban Sensing | 34 | 7 | 27 | 20.6% |
| 01h8v8qt | Coping with irregular spatio-temporal sampling in sensor networks | 33 | 9 | 24 | 27.3% |
| 4kw5x35z | Timing-sync protocol for sensor networks | 33 | 21 | 12 | 63.6% |
| 7fs3g0c5 | Long-lived solid state perchlorate ion selective sensor based on doped poly(3,4-ethylenedioxythiophene) (PEDOT) films | 33 | 4 | 29 | 12.1% |
| 9wm343pn | Sharing Sensor Network Data | 33 | 2 | 31 | 6.1% |
| 77d882tk | Adaptive Sampling for Environmental Robotics | 32 | 16 | 16 | 50.0% |
| 5pt8v7b2 | High Resolution River Hydraulic and Water Quality Characterization Using Rapidly Deployable Networked Infomechanical Systems (NIMS RD) | 30 | 10 | 20 | 33.3% |
| 20f0w8wn | New Visualization Tools for Environmental Sensor Networks: Using Google Earth as an Interface to Micro-Climate and Multimedia Datasets | 28 | 5 | 23 | 17.9% |
| 97x201c3 | Computation Hierarchy for In-network processing | 28 | 18 | 10 | 64.3% |
| 6qt7q51z | Information-Theoretic Approaches for Sensor Selection and Placement in Sensor Networks for Target Localization and Tracking | 27 | 2 | 25 | 7.4% |
| 73k4d7cz | A Unified Network and Node Level Simulation Framework for Wireless Sensor Networks | 27 | 8 | 19 | 29.6% |
| 9s9717fw | EmStar: a Software Environment for Developing and Deploying Wireless Sensor Networks | 27 | 5 | 22 | 18.5% |
| 0k03m88d | Optimal and Global Time Synchronization in Sensornets | 26 | 7 | 19 | 26.9% |
| 41b2k7b6 | Tenet: An Architecture for Tiered Embedded Networks | 26 | 4 | 22 | 15.4% |
| 91v6t8j2 | Actuation Techniques for Sensing Uncertainty Reduction | 26 | 5 | 21 | 19.2% |
| 2446x3n4 | Self-configuring Localization Systems: Design and Experimental Evaluation | 25 | 5 | 20 | 20.0% |
| 5j74t2g2 | Sensor Network Data Fault Detection using Hierarchical Bayesian Space-Time Modeling | 25 | 4 | 21 | 16.0% |
| 28v8b7c9 | The Final Frontier: Embedding Networked Sensors in the Soil | 24 | 4 | 20 | 16.7% |
| 5h22d6xv | EmStar: An Environment for Developing Wireless Embedded Systems Software | 23 | 20 | 3 | 87.0% |
| 1f27k34v | Efficient and Practical Query Scoping in Sensor Networks | 22 | 5 | 17 | 22.7% |
| 5qm2r7px | Optimal Spectrum Management in Multiuser Interference Channels | 22 | 3 | 19 | 13.6% |
| 6gm8q0pc | Towards Event-Aware Adaptive Sampling Using Static and Mobile Nodes | 21 | 2 | 19 | 9.5% |
| 0h69t3ng | A Platform for Collaborative Acoustic Signal Processing | 20 | 3 | 17 | 15.0% |
| 2s2878kf | Use more realistic data models to evaluate sensor network data processing algorithms | 20 | 1 | 19 | 5.0% |
| 3s75m359 | Data Modeling and Synthetic Data Generation For Fine-Grained Networked Sensing | 20 | 2 | 18 | 10.0% |
| 53j47623 | IDEA: Iterative experiment Design for Environmental Applications | 20 | 5 | 15 | 25.0% |
| 8823t1n2 | Heartbeat of a Nest: Using Imagers as Biological Sensors | 20 | 5 | 15 | 25.0% |
| 2g49z78g | SCALE: A tool for Simple Connectivity Assessment in Lossy Environments | 19 | 7 | 12 | 36.8% |
| 9nv096c4 | Mote Herding for Tiered Wireless Sensor Networks | 19 | 4 | 15 | 21.1% |
| 2zs0d08c | Sensing Uncertainty Reduction Using Low Complexity Actuation | 18 | 3 | 15 | 16.7% |
| 3v07x98q | Fidelity and Resource Sensitive Data Gathering | 18 | 2 | 16 | 11.1% |
| 6tt8g446 | Real-time Model Parameter Estimation for Analyzing Transport in Porous Media | 18 | 0 | 18 | 0.0% |
| 6sj003r4 | Wireless Urban Sensing Systems | 17 | 6 | 11 | 35.3% |
| 3fq8x53k | Genetic Algorithm-Based Embedded Networked Sensing Design Coupled to an Environmental Simulator | 16 | 2 | 14 | 12.5% |
| 5qf724x3 | On Scalability and Source/Channel Coding Decoupling in Large Scale Sensor Networks | 16 | 2 | 14 | 12.5% |
| 7391w3v2 | Reliability and Storage in Sensor Networks | 16 | 3 | 13 | 18.8% |
Note: Due to the evolving nature of web traffic, the data presented here should be considered approximate and subject to revision. Learn more.