Change search
Link to record
Permanent link

Direct link
Publications (10 of 75) Show all publications
He, Y., Wang, W., Mottola, L., Li, S., Sun, Y., Li, J., . . . Wang, Y. (2024). Acoustic Localization System for Precise Drone Landing. IEEE Transactions on Mobile Computing, 23(5), 4126-4144
Open this publication in new window or tab >>Acoustic Localization System for Precise Drone Landing
Show others...
2024 (English)In: IEEE Transactions on Mobile Computing, Vol. 23, no 5, p. 4126-4144Article in journal (Refereed) Published
Abstract [en]

We present MicNest: an acoustic localization system enabling precise drone landing. In MicNest, multiple microphones are deployed on a landing platform in carefully devised configurations. The drone carries a speaker transmitting purposefully-designed acoustic pulses. The drone may be localized as long as the pulses are correctly detected. Doing so is challenging: i) because of limited transmission power, propagation attenuation, background noise, and propeller interference, the Signal-to-Noise Ratio (SNR) of received pulses is intrinsically low; ii) the pulses experience non-linear Doppler distortion due to the physical drone dynamics; iii) as location information is used during landing, the processing latency must be reduced to effectively feed the flight control loop. To tackle these issues, we design a novel pulse detector, Matched Filter Tree (MFT), whose idea is to convert pulse detection to a tree search problem. We further present three practical methods to accelerate tree search jointly. Our experiments show that MicNest can localize a drone 120 m away with 0.53% relative localization error at 20 Hz location update frequency. For navigating drone landing, MicNest can achieve a success rate of 94 %. The average landing error (distance between landing point and target point) is only 4.3 cm.

National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:ri:diva-69241 (URN)10.1109/tmc.2023.3288299 (DOI)
Note

This work is partially supported by the National Science Fund of Chinaunder grant No. U21B2007, Tsinghua University - Meituan Joint Institutefor Digital Life, the Swedish Science Foundation (SSF), the Digital Futuresprogramme (project Drone Arena), the Swedish Research Council, and KAWproject UPDATE

Available from: 2024-01-09 Created: 2024-01-09 Last updated: 2024-06-11Bibliographically approved
Singhal, C., Voigt, T. & Mottola, L. (2023). Application-aware Energy Attack Mitigation in the Battery-less Internet of Things. In: MobiWac 2023: Proceedings of the International ACM Symposium on Mobility Management and Wireless Access. Paper presented at MSWiM '23: Int'l ACM Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems (pp. 35-43). Association for Computing Machinery, Inc
Open this publication in new window or tab >>Application-aware Energy Attack Mitigation in the Battery-less Internet of Things
2023 (English)In: MobiWac 2023: Proceedings of the International ACM Symposium on Mobility Management and Wireless Access, Association for Computing Machinery, Inc , 2023, p. 35-43Conference paper, Published paper (Refereed)
Abstract [en]

We study how to mitigate the effects of energy attacks in the battery-less Internet of Things∼(IoT). Battery-less IoT devices live and die with ambient energy, as they use energy harvesting to power their operation. They are employed in a multitude of applications, including safety-critical ones such as biomedical implants. Due to scarce energy intakes and limited energy buffers, their executions become intermittent, alternating periods of active operation with periods of recharging their energy buffers. Experimental evidence exists that shows how controlling ambient energy allows an attacker to steer a device execution in unintended ways: energy provisioning effectively becomes an attack vector. We design, implement, and evaluate a mitigation system for energy attacks. By taking into account the specific application requirements and the output of an attack detection module, we tune task execution rates and optimize energy management. This ensures continued application execution in the event of an energy attack. When a device is under attack, our solution ensures the execution of 23.3% additional application cycles compared to the baselines we consider and increases task schedulability by at least 21%, while enabling a 34% higher peripheral availability. 

Place, publisher, year, edition, pages
Association for Computing Machinery, Inc, 2023
Keywords
Internet of things; Safety engineering; Secondary batteries; Ambients; Battery-less; Battery-less iot application; Energy; Energy-attack mitigation; Federated energy harvesting; Intermittent computing; IOT applications; Power; Tasks scheduling; Energy harvesting
National Category
Computer Systems Communication Systems
Identifiers
urn:nbn:se:ri:diva-68773 (URN)10.1145/3616390.3618281 (DOI)2-s2.0-85178079293 (Scopus ID)
Conference
MSWiM '23: Int'l ACM Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems
Funder
Swedish Foundation for Strategic Research
Available from: 2024-01-15 Created: 2024-01-15 Last updated: 2024-01-15Bibliographically approved
Shen, Q., Mahima, K., de Zoysa, K., Mottola, L., Voigt, T. & Flierl, M. (2023). CNN-Based Estimation of Water Depth from Multispectral Drone Imagery for Mosquito Control. In: 2023 IEEE International Conference on Image Processing (ICIP): . Paper presented at 2023 IEEE International Conference on Image Processing (ICIP) (pp. 3250-3254). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>CNN-Based Estimation of Water Depth from Multispectral Drone Imagery for Mosquito Control
Show others...
2023 (English)In: 2023 IEEE International Conference on Image Processing (ICIP), Institute of Electrical and Electronics Engineers (IEEE), 2023, p. 3250-3254Conference paper, Published paper (Refereed)
Abstract [en]

We present a machine learning approach that uses a custom Convolutional Neural Network (CNN) for estimating the depth of water pools from multispectral drone imagery. Using drones to obtain this information offers a cheaper, timely, and more accurate solution compared to alternative methods, such as manual inspection. This information, in turn, represents an asset to identify potential breeding sites of mosquito larvae, which grow only in shallow water pools. As a significant part of the world’s population is affected by mosquito-borne viral infections, including Dengue and Zika, identifying mosquito breeding sites is key to control their spread. Experiments with 5-band drone imagery show that our CNN-based approach is able to measure shallow water depths accurately up to a root mean square error of less than 0.5 cm, outperforming state-of-the-art Random Forest methods and empirical approaches.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:ri:diva-68550 (URN)10.1109/ICIP49359.2023.10222934 (DOI)
Conference
2023 IEEE International Conference on Image Processing (ICIP)
Note

This work has been partly funded by Digital Futures and the SwedishResearch Council (Grant 2018-05024) 

Available from: 2023-12-13 Created: 2023-12-13 Last updated: 2023-12-13Bibliographically approved
Mahima, K. T., Weerasekara, M., Zoysa, K. D., Keppitiyagama, C., Flierl, M., Mottola, L. & Voigt, T. (2023). MM4Drone: A Multi-spectral Image and mmWave Radar Approach for Identifying Mosquito Breeding Grounds via Aerial Drones. In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST: . Paper presented at 16th EAI International Conference on Pervasive Computing Technologies for Healthcare, PH 2022. Thessaloniki, Greece. 12 December 2022 through 14 December 2022 (pp. 412-426). Springer Science and Business Media Deutschland GmbH, 488
Open this publication in new window or tab >>MM4Drone: A Multi-spectral Image and mmWave Radar Approach for Identifying Mosquito Breeding Grounds via Aerial Drones
Show others...
2023 (English)In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Springer Science and Business Media Deutschland GmbH , 2023, Vol. 488, p. 412-426Conference paper, Published paper (Refereed)
Abstract [en]

Mosquitoes spread disases such as Dengue and Zika that affect a significant portion of the world population. One approach to hamper the spread of the disases is to identify the mosquitoes’ breeding places. Recent studies use drones to detect breeding sites, due to their low cost and flexibility. In this paper, we investigate the applicability of drone-based multi-spectral imagery and mmWave radios to discover breeding habitats. Our approach is based on the detection of water bodies. We introduce our Faster R-CNN-MSWD, an extended version of the Faster R-CNN object detection network, which can be used to identify water retention areas in both urban and rural settings using multi-spectral images. We also show promising results for estimating extreme shallow water depth using drone-based multi-spectral images. Further, we present an approach to detect water with mmWave radios from drones. Finally, we emphasize the importance of fusing the data of the two sensors and outline future research directions. 

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2023
Keywords
Aerial Drones, mmWave Radar, Multispectral Imagery, Object Detection, Aircraft detection, Antennas, Drones, Millimeter waves, Object recognition, Radar imaging, Tracking radar, Aerial drone, Breeding grounds, Low-costs, Mm waves, Mosquito breeding, Multispectral images, Objects detection, World population
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:ri:diva-65700 (URN)10.1007/978-3-031-34586-9_27 (DOI)2-s2.0-85164166242 (Scopus ID)9783031345852 (ISBN)
Conference
16th EAI International Conference on Pervasive Computing Technologies for Healthcare, PH 2022. Thessaloniki, Greece. 12 December 2022 through 14 December 2022
Note

This work has been partly funded by Digital Futures and the Swedish Research Council (Grant 2018-05024).

Available from: 2023-08-11 Created: 2023-08-11 Last updated: 2023-08-11Bibliographically approved
Maioli, A. & Mottola, L. (2021). ALFRED: Virtual Memory for Intermittent Computing. In: Proceedings of the 19th ACM International Conference on Embedded Networked Sensor Systems (SENSYS), Coimbra (Portugal), November 2021.: . Paper presented at 19th ACM International Conference on Embedded Networked Sensor Systems (SENSYS), Coimbra (Portugal), November 2021..
Open this publication in new window or tab >>ALFRED: Virtual Memory for Intermittent Computing
2021 (English)In: Proceedings of the 19th ACM International Conference on Embedded Networked Sensor Systems (SENSYS), Coimbra (Portugal), November 2021., 2021Conference paper, Published paper (Other academic)
Abstract [en]

We present ALFRED: a virtual memory abstraction that resolves the dichotomy between volatile and non-volatile memory in intermittent computing. Mixed-volatile microcontrollers allow programmers to allocate part of the application state onto non-volatile memory. Programmers are therefore to manually explore the tradeoff between simpler management of persistent state against energy overhead and possibility of intermittence anomalies due to nonvolatile memory operations. This approach is laborious and yields sub-optimal performance. We take a different stand with ALFRED: we provide programmers with a virtual memory abstraction detached from the specific volatile nature of memory and automatically determine an efficient mapping from virtual to volatile or non-volatile memory. Unlike existing works, ALFRED does not require programmers to learn a newlanguage syntax and the mapping is entirely resolved at compile-time, reducing the run-time energy overhead.We implement ALFRED through a series of machine-level code transformations. Compared to existing systems, we demonstrate that ALFRED reduces energy consumption by up to two orders of magnitude given a fixed workload. This enables workloads to finish sooner, as the use of available energy shifts from ensuring forward progress to useful application processing.

National Category
Computer Sciences
Identifiers
urn:nbn:se:ri:diva-58788 (URN)
Conference
19th ACM International Conference on Embedded Networked Sensor Systems (SENSYS), Coimbra (Portugal), November 2021.
Available from: 2022-03-03 Created: 2022-03-03 Last updated: 2023-05-25Bibliographically approved
Maioli, A., Mottola, L., Hamad Alizai, M. & Haroon Siddiqui, J. (2021). Discovering the Hidden Anomalies of Intermittent Computing. In: Proceedings of the 18th ACM International Conference on Embedded Wireless Systems and Networks (EWSN), Delft (The Netherlands), February 2021.: . Paper presented at 18th ACM International Conference on Embedded Wireless Systems and Networks (EWSN), Delft (The Netherlands), February 2021..
Open this publication in new window or tab >>Discovering the Hidden Anomalies of Intermittent Computing
2021 (English)In: Proceedings of the 18th ACM International Conference on Embedded Wireless Systems and Networks (EWSN), Delft (The Netherlands), February 2021., 2021Conference paper, Published paper (Other academic)
Abstract [en]

Energy harvesting battery-less embedded devices compute intermittently, as energy is available. Intermittent executions may differ from continuous ones due to repeated executions of non-idempotent code. This anomaly is normally recognized as a “bug” and solutions exist to retain equivalence between intermittent and continuous executions. We argue that our current understanding of these “bugs” is limited. We address this issue by devising techniques to comprehensively identify where and how intermittent and continuous executions possibly differ and by implementing them in SCEPTIC: a code analysis tool for intermittent programs. Thereby, we find execution anomalies and their manifested impact on program behavior in ways previously not considered. This analysis is enabled by SCEPTIC design, implementation, and performance. SCEPTIC runs up to ten orders of magnitude faster than the baselines we consider, enabling many types of analyses that would be otherwise impractical.

National Category
Computer Sciences
Identifiers
urn:nbn:se:ri:diva-58787 (URN)
Conference
18th ACM International Conference on Embedded Wireless Systems and Networks (EWSN), Delft (The Netherlands), February 2021.
Available from: 2022-03-03 Created: 2022-03-03 Last updated: 2023-05-25Bibliographically approved
Zimmerling, M., Mottola, L. & Santini, S. (2021). Synchronous Transmissions in Low-Power Wireless: A Survey of Communication Protocols and Network Services. ACM Computing Surveys, 53(6), Article ID 121.
Open this publication in new window or tab >>Synchronous Transmissions in Low-Power Wireless: A Survey of Communication Protocols and Network Services
2021 (English)In: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 53, no 6, article id 121Article in journal (Refereed) Published
Abstract [en]

Low-power wireless communication is a central building block of cyber-physical systems and the Internet of Things. Conventional low-power wireless protocols make avoiding packet collisions a cornerstone design choice. The concept of synchronous transmissions challenges this view. As collisions are not necessarily destructive, under specific circumstances, commodity low-power wireless radios are often able to receive useful information even in the presence of superimposed signals from different transmitters. We survey the growing number of protocols that exploit synchronous transmissions for higher robustness and efficiency as well as unprecedented functionality and versatility compared to conventional designs. The illustration of protocols based on synchronous transmissions is cast in a conceptional framework we establish, with the goal of highlighting differences and similarities among the proposed solutions. We conclude this article with a discussion on open questions and challenges in this research field

Place, publisher, year, edition, pages
Association for Computing Machinery, 2021
Keywords
capture effect, constructive interference, Low-power wireless networks, message-in-message effect, multi-hop communication, sender diversity, simplicity, synchronous transmissions, Embedded systems, Radio transmission, Surveys, Building blockes, Conventional design, Low power wireless, Low-power wireless communications, Network services, Packet collisions, Superimposed signal, Synchronous transmission, Low power electronics
National Category
Communication Systems
Identifiers
urn:nbn:se:ri:diva-52493 (URN)10.1145/3410159 (DOI)2-s2.0-85100711850 (Scopus ID)
Available from: 2021-03-18 Created: 2021-03-18 Last updated: 2023-05-25Bibliographically approved
Afanasov, M., Bhatti, N., Campagna, D., Caslini, G., Centonze, F., Dolui, K., . . . Mottola, L. (2020). Battery-less zero-maintenance embedded sensing at the mithræum of circus maximus. In: SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems: . Paper presented at 18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020, 16 November 2020 through 19 November 2020 (pp. 368-381). Association for Computing Machinery, Inc
Open this publication in new window or tab >>Battery-less zero-maintenance embedded sensing at the mithræum of circus maximus
Show others...
2020 (English)In: SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems, Association for Computing Machinery, Inc , 2020, p. 368-381Conference paper, Published paper (Refereed)
Abstract [en]

We present the design and evaluation of a 3.5-year embedded sensing deployment at the Mithræum of Circus Maximus, a UNESCO-protected underground archaeological site in Rome (Italy). Unique to our work is the use of energy harvesting through thermal and kinetic energy sources. The extreme scarcity and erratic availability of energy, however, pose great challenges in system software, embedded hardware, and energy management. We tackle them by testing, for the first time in a multi-year deployment, existing solutions in intermittent computing, low-power hardware, and energy harvesting. Through three major design iterations, we find that these solutions operate as isolated silos and lack integration into a complete system, performing suboptimally. In contrast, we demonstrate the efficient performance of a hardware/software co-design featuring accurate energy management and capturing the coupling between energy sources and sensed quantities. Installing a battery-operated system alongside also allows us to perform a comparative study of energy harvesting in a demanding setting. Albeit the latter reduces energy availability and thus lowers the data yield to about 22% of that provided by batteries, our system provides a comparable level of insight into environmental conditions and structural health of the site. Further, unlike existing energy-harvesting deployments that are limited to a few months of operation in the best cases, our system runs with zero maintenance since almost 2 years, including 3 months of site inaccessibility due to a COVID19 lockdown

Place, publisher, year, edition, pages
Association for Computing Machinery, Inc, 2020
Keywords
energy harvesting, intermittent computing, low-power hardware, Electric batteries, Embedded systems, Energy efficiency, Energy management, Hardware-software codesign, Kinetic energy, Kinetics, Archaeological site, Battery-operated systems, Comparative studies, Design and evaluations, Energy availability, Environmental conditions, Lowpower hardware, Structural health
National Category
Natural Sciences
Identifiers
urn:nbn:se:ri:diva-51701 (URN)10.1145/3384419.3430722 (DOI)2-s2.0-85097519446 (Scopus ID)9781450375900 (ISBN)
Conference
18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020, 16 November 2020 through 19 November 2020
Note

Funding details: Stiftelsen för Strategisk Forskning, SSF; Funding details: Google; Funding text 1: The hardware schematics and application code for the three design iterations are available [2] for the community to build on. Acknowledgments. We thank the shepherd and reviewers for the feedback received on the initial submission. This work was supported partly by the Google Faculty Award programme and by the Swedish Foundation for Strategic Research (SSF).

Available from: 2021-01-08 Created: 2021-01-08 Last updated: 2023-05-25Bibliographically approved
Ahmed, S., Nawaz, M., Bakar, A., Bhatti, N. A., Alizai, M. H., Siddiqui, J. H. & Mottola, L. (2020). Demystifying Energy Consumption Dynamics in Transiently Powered Computers. ACM Transactions on Embedded Computing Systems, 19(6), Article ID 47.
Open this publication in new window or tab >>Demystifying Energy Consumption Dynamics in Transiently Powered Computers
Show others...
2020 (English)In: ACM Transactions on Embedded Computing Systems, ISSN 1539-9087, E-ISSN 1558-3465, Vol. 19, no 6, article id 47Article in journal (Refereed) Published
Abstract [en]

Transiently powered computers (TPCs) form the foundation of the battery-less Internet of Things, using energy harvesting and small capacitors to power their operation. This kind of power supply is characterized by extreme variations in supply voltage, as capacitors charge when harvesting energy and discharge when computing. We experimentally find that these variations cause marked fluctuations in clock speed and power consumption. Such a deceptively minor observation is overlooked in existing literature. Systems are thus designed and parameterized in overly conservative ways, missing on a number of optimizations.We rather demonstrate that it is possible to accurately model and concretely capitalize on these fluctuations. We derive an energy model as a function of supply voltage and prove its use in two settings. First, we develop EPIC, a compile-time energy analysis tool. We use it to substitute for the constant power assumption in existing analysis techniques, giving programmers accurate information on worst-case energy consumption of programs. When using EPIC with existing TPC system support, run-time energy efficiency drastically improves, eventually leading up to a 350% speedup in the time to complete a fixed workload. Further, when using EPIC with existing debugging tools, it avoids unnecessary program changes that hurt energy efficiency. Next, we extend the MSPsim emulator and explore its use in parameterizing a different TPC system support. The improvements in energy efficiency yield up to more than 1000% time speedup to complete a fixed workload.

Place, publisher, year, edition, pages
Association for Computing Machinery, 2020
Keywords
intermittent computing, Transiently powered computers, energy modelling
National Category
Natural Sciences
Identifiers
urn:nbn:se:ri:diva-49114 (URN)10.1145/3391893 (DOI)
Note

This research has been partially supported by the Swedish Foundation for Strategic Research (SSF).

Available from: 2020-10-13 Created: 2020-10-13 Last updated: 2023-05-25Bibliographically approved
Ahmed, S., Bhatti, N., Alizai, H., Siddiqui, J. & Mottola, L. (2020). Fast and Energy-Efficient State Checkpointing for Intermittent Computing. ACM Transactions on Embedded Computing Systems, 19(6), Article ID 45.
Open this publication in new window or tab >>Fast and Energy-Efficient State Checkpointing for Intermittent Computing
Show others...
2020 (English)In: ACM Transactions on Embedded Computing Systems, ISSN 1539-9087, E-ISSN 1558-3465, Vol. 19, no 6, article id 45Article in journal (Refereed) Published
Abstract [en]

Intermittently powered embedded devices ensure forward progress of programs through state checkpointing in non-volatile memory. Checkpointing is, however, expensive in energy and adds to the execution times. To minimize this overhead, we present DICE, a system that renders differential checkpointing profitable on these devices. DICE is unique because it is a software-only technique and efficient because it only operates in volatile main memory to evaluate the differential. DICE may be integrated with reactive (Hibernus) or proactive (MementOS, HarvOS) checkpointing systems, and arbitrary code can be enabled with DICE using automatic code-instrumentation requiring no additional programmer effort. By reducing the cost of checkpoints, DICE cuts the peak energy demand of these devices, allowing operation with energy buffers that are one-eighth of the size originally required, thus leading to benefits such as smaller device footprints and faster recharging to operational voltage level. The impact on final performance is striking: with DICE, Hibernus requires one order of magnitude fewer checkpoints and one order of magnitude shorter time to complete a workload in real-world settings.

Place, publisher, year, edition, pages
Association for Computing Machinery, 2020
Keywords
differential checkpointing, intermittent computing, Transiently powered computers, Digital storage, Automatic codes, Embedded device, Energy efficient, Non-volatile memory, Operational voltage, Peak energy demand, Real world setting, Software-only techniques, Energy efficiency
National Category
Natural Sciences
Identifiers
urn:nbn:se:ri:diva-51202 (URN)10.1145/3391903 (DOI)2-s2.0-85097331607 (Scopus ID)
Note

Funding details: Stiftelsen för Strategisk Forskning, SSF; Funding text 1: This research has been partially supported by the Swedish Foundation for Strategic Research (SSF).

Available from: 2021-01-07 Created: 2021-01-07 Last updated: 2023-05-25Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-4560-9541

Search in DiVA

Show all publications