Wireless Systems for a Sustainable Future: From Battery-Free Subsea IoT to THz-Based Agriculture Monitoring

This thesis describes how wireless sensing can drive significant advancements in climate and sustainability. Specifically, it shows how we can leverage diverse signals—acoustics, ultrasound, THz, and optics— in unconventional ways to unlock new capabilities in underwater climate monitoring, food safety, and disaster response. The thesis introduces two novel technologies. The first technology enables long-term, ultra-low power ocean sensor networks for use in climate modeling, marine monitoring, and sustainable aquaculture. Unlike existing IoT technologies – like Bluetooth, WiFi, and GPS – which cannot work underwater, we design and implement an ultra-low power subsea backscatter communication system, enabling battery-free underwater imaging, sensing and localization. Second, the thesis describes a new technology that can support sustainability in agriculture through real-time food quality assessment that reduces food waste. In contrast to existing food quality technologies that require direct contact with produce, we introduce a new wireless system for accurate, non-invasive sensing using sub-THz signals. We describe the design, implementation, and evaluation of multiple systems that leverage these technologies to monitor the ocean and food waste: First, we present a ultra-wideband metamaterial sensor design that facilitates scalable, and long-range battery-free underwater communication. Next, we describe a system that can push the throughput of this technology using higher order modulation. Beyond building sensor networks, we demonstrate their real-world potential through two systems: one for underwater localization that uses rich spatio-temporal-spectral features for accurate positioning, and another for battery-free imaging that fuses acoustic and optical signals to capture color images in the dark. Finally, we present a novel solution for accurate fruit ripeness sensing using sub-terahertz wireless signals. These systems unlock new IoT applications in climate modeling, aquaculture, robotics, and agriculture.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2025

Author dc:creator

• Afzal, Sayed Saad

Advisor dc:contributor.advisor

• Adib, Fadel

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/164052

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/164052